empathy at work

This week Meta notified approximately 8,000 employees — roughly 10% of its workforce — that their positions were being eliminated, part of a sweeping restructuring the company has framed as necessary to fund its push into artificial intelligence. At the same time, 7,000 workers are being redirected into newly created AI-focused teams. The stated rationale is efficiency, investment, and building an AI-first organization.

I feel for the people who lost their jobs, and the communities who may be impacted by that large number of people being out of work. It it also gives me pause about how the company is redesigning work, with particular attention on human skills such as empathy, out of the work itself.

What Gets MIssed When Work is Redesigned Around Tasks Alone

When companies restructure around AI, the decisions are typically made at the level of structure and budget: headcount targets, function eliminations, and capital redirected from people to infrastructure. What is often not captured are the human skills embedded inside the work itself: the employee who senses what a customer needs before they say it, who hears the unvoiced question, and who finds the right words at the right moment to turn a frustrated caller into a loyal one.

Those human skills do not appear on a process map or show up in a task description. When the function is eliminated, they walk out the door with the people who held them, and may gradually be designed out of the jobs of the people who remain. Nobody budgeted for that loss. But the customer feels it fast.

What AI Cannot Do

We are humans before we are customers, before we are employees, before we are stakeholders. Emotions are our native language and they predate every other language we have ever developed. Long before human civilization developed words, people communicated danger, grief, and belonging through what they felt and what they read in others. As infants we communicate fear, hunger, comfort, and joy long before we have words for any of them, and the people around us learn to read those signals with extraordinary precision. That capacity does not leave us when language arrives. That is the foundation of human connection itself. AI was built on language. It has no access to the layer of human experience that exists before words form.

AI can define empathy, explain the research behind it, and describe how it functions in organizational settings. What it cannot do is feel it, and what it cannot do is intuit what to do about it in the specific, contextual, human moment when it matters. A leader sitting with a customer who feels dismissed, an employee who is frightened, or a partner who feels squeezed, is navigating something no algorithm can fully read. The human skills required in that moment are developed over time, through experience and attention and they are what no model can learn to feel.

The Cost of Getting It Wrong

The dominant framework sorted skills into two categories: technical skills (formerly called hard skills), considered measurable and therefore serious, and human skills (formerly called soft skills), everything else. What could be measured became synonymous with what mattered, and everything else was diminished. For anyone whose greatest strengths lived in the human rather than the technical domain, the message from organizations was that those strengths did not carry the same value. Contemporary management research has consistently revealed the importance of human skills such as empathy, communication, collaboration, emotional regulation, and judgment. Peter Drucker saw this clearly. "Management is a Liberal Art," he wrote in 1989, liberal because it deals with knowledge, self-knowledge, wisdom, and leadership; art because it deals with practice and application. Managers, he argued, must draw on psychology, philosophy, economics, ethics, and the humanities, and focus that knowledge on effectiveness and results.

We have devalued human wisdom and skills before. We know what it costs. The losses surface in the numbers, in eroding relationships, in customer and employee experience, and in the partnerships that dissolve when people no longer feel respected. With the urgency and scale of AI adoption, we risk repeating that devaluation faster than we can recognize it. Which is precisely why the signals already present in every organization deserve more attention, not less.

Named or Not, Emotions Are in the Room

Emotions are present in every organization, driving behavior, shaping how customers decide, how employees perform, and how vendor relationships hold or fracture under pressure. Leaders who cannot read them are making decisions with incomplete information. Warning lights do not stop flashing because you tape over them, and an organization that has trained itself to ignore emotional signals is not operating without that data. It is simply operating without access to it.

The Dashboard Every Leader Needs

Think of emotions as dashboard indicator lights for human needs. When needs are met, the lights are green: trust, engagement, loyalty, collaboration. When needs go unmet, warning lights flash: frustration, disengagement, churn, conflict. The people in your organization who can see the world through another person's eyes, anticipate needs before they are voiced, and find the right words at the right moment are your most valuable readers of that dashboard. Empathy is what allows a leader to see which needs are being met and do more of that, and to see which needs are not being met and work to address them.

Customers need to feel heard, respected, and reliably supported. Employees need clarity, psychological safety, and the sense that their contribution matters. Vendors and partners need to know that the relationship is fair and that their expertise is trusted. When these needs are met, the results are visible: loyalty, engagement, partnership, advocacy. When they go unmet, the costs accumulate in ways that rarely appear on the original task audit with churn, turnover, reputational damage, and the slow erosion of the organizational trust that makes execution possible. Leaders who dismiss emotions as irrelevant are missing the data they need to sustain loyalty with customers, build trust with employees, and maintain strong partnerships with vendors.

Empathy in Practice

Here are three practices to sharpen individual and organizational empathy:

• Ask people how they are feeling, and mean it. The people in your organization possess information that will not appear in any report, and the only way to access it is to create the conditions in which they feel safe enough to share it.

• Listen carefully to those who are putting emotions into words. They are not being difficult. They are giving you access to the organizational intelligence you need to make better decisions.

• As you consider if, how, and when AI tools are integrated into your organization, take a full accounting of the human skills associated with each role, not to automate them, but to understand the what the organization depends on and protect it accordingly.

Technical skills and human skills are interdependent. A strategy without the trust to execute it is a document. A financial model without the judgment to interpret it is a spreadsheet. An AI implementation without the empathy to understand what customers, employees, and partners actually need from it is an expensive source of new problems.

When technology serves human effectiveness, relationships, and organizational health, it fulfills its purpose. That is the standard worth holding: for every tool you adopt, every role you redesign, and every decision you make about how work gets done. Empathy is what keeps that standard visible.

IN TIMES OF UNCERTAINTY, WHAT CAN YOU CONTOL?

If I were to choose one word five months into 2026, that word is uncertainty.

The U.S. is navigating war, immigration policy changes and labor uncertainty, tariffs, funding instability, economic pressure, rising costs for healthcare, food, energy and transportation, the use of AI, and deepening social division.

It’s a lot.

For individuals and organizations, periods like this require us to think carefully about three categories:

• What is within our direct control?

• What can we influence, even if we do not control the outcome?

• And what must we acknowledge is outside our control altogether?

If we do not consider these questions, we run the danger of exhausting ourselves trying to control conditions we have no ability to control, while overlooking the areas where our actions genuinely matter.

Pay Attention to What Has Your Attention

Here is a simple exercise to help you get clear on where you should focus.

What currently has your attention?

•          Which of these contribute to your sense of well-being?

•          Which of these add stress?

•          Which of these are within your direct control?

•          Which of these can you influence?

•          Which of these are outside your control altogether?

For the things within your control, the goal is to strengthen your response, your preparation, your priorities, and your habits.

For the things you can influence, the goal is contribution. You may not control the final outcome, but your preparation, perspective, communication, and actions can still shape how people think, respond, and move forward.

Your boss may make the final decision. A customer may choose a different direction. A community issue may not be resolved immediately. Even so, thoughtful input and responsible action still matter.

And then there are situations, such as natural disasters or geopolitical conflict, where we may have little ability to influence the immediate condition itself. Even there, we still retain some control over our response and preparation, like having an earthquake kit in your car and home.

Leaders Navigate Uncertainty on Multiple Levels

Leaders face the same external conditions everyone else does. They must also assess what those conditions mean for the organization on a variety of levels — operationally, strategically, financially, culturally — and understand how that organizational reality is landing on the people responsible for executing the work.

AI, Overload, and Organizational Strain

This assessment becomes especially important as organizations continue integrating AI into the workplace.

A leader may look at an overwhelmed workforce and conclude that this is the perfect moment to introduce AI to reduce workload.

Effective AI depends on human oversight, and the people providing that oversight must have time for:

•          critical thinking

•          verification

•          contextual judgment

•          reflection

•          prioritization

•          ethical considerations

All of those capacities require time and tend to weaken under chronic stress, excessive workload, and constant pressure, making overload one of the worst conditions for responsible AI use.

When people are overwhelmed, the temptation increases to accept the first answer, skip validation, rely on summaries instead of deeper understanding, or use AI to move faster without fully thinking through the implications.

The Use of AI Can Amplify Organizational Strain, Not Relieve It

In a recent Harvard Business Review IdeaCast episode, “The Hidden Causes of AI Workslop—and How to Fix Them,” Kate Niederhoffer, chief scientist at BetterUp, and Jeff Hancock, professor of communication at Stanford, discuss the rise of what they called “AI work slop,” low-quality work produced when employees rely heavily on AI outputs without sufficient verification, reflection, or original thinking.

Hancock and Niederhoffer are direct that “workslop” is often a symptom of organizational conditions, including general AI mandates and pressure to do more work because AI tools are available.

If the underlying conditions of the organization remain unclear priorities, unrealistic workloads, constant urgency, fragmented communication, and insufficient capacity, AI may accelerate the symptoms without resolving the causes.

The inverse is also true. When priorities are clear, workloads are realistic, and capacity exists, people can bring the judgment and care that responsible AI use requires.

THE ALIGN Method

In times of uncertainty, the ALIGN Method can help organizations navigate complexity without overwhelming the people inside them.

ABSORB: Understand Current Reality

The ALIGN method begins with ABSORB. Before leaders can set priorities or introduce change, they need an honest picture of current reality — not just operationally, but humanly. That requires asking specific questions and listening deeply, without judgment.

Leaders take in both the concrete information being shared and the emotions accompanying it. They pay attention to what people are experiencing, what pressures they are carrying, what concerns are surfacing repeatedly, and where capacity may already be strained.

Listening to a variety of perspectives helps leadership better understand both operational reality and the organization’s tolerance for change. There is often an inverse relationship between stress and tolerance for change. As stress rises, people generally have less capacity for additional uncertainty, ambiguity, or disruption.

If employees are already carrying significant pressure from conditions outside the organization’s control, leaders should carefully examine what can realistically be absorbed before introducing large amounts of additional change internally.

LEGITIMIZE: Set Priorities Responsibly

Before leaders can set organizational priorities, they have to reckon with what they are carrying. Leaders are not personally above the uncertainty. They face the same external pressures as everyone else, carry additional pressures that come with the role, and are still responsible for understanding and responding to what their people are experiencing.

After listening to stakeholders, leaders need to make sense of the information that was gathered and determine the priorities for the organization to focus on. By identifying priorities, leadership has assessed what can realistically be carried forward without overwhelming the people responsible for execution.

INTEGRATE: Translate Priorities Into Operations

Priorities handed down from above don’t always account for how work actually gets done. INTEGRATE is where that gap surfaces. By involving the people most impacted by the work, leadership gains an honest picture of what execution actually requires — including the workarounds, constraints, and realities that never make it into a strategy document.

Communication remains essential during this phase. Employees need space to identify conflicts, surface unintended consequences, and help leadership understand what the work actually requires in practice.

GROW: Build Capacity and Capability

There is a story from Mencius, a Chinese philosopher, of a farmer who wanted his crops to grow faster, so he pulled the seedlings upward to help them along. Shortly after, they were all dead.

The impulse to accelerate is understandable. It is part of why organizations reach for AI.

However growth cannot be forced.

In ALIGN, GROW is the phase where the organization builds the capability and capacity required to support the work through learning, coaching, communication, skill building, and ongoing support.

This phase requires leaders to pay attention to burnout, overload, and unrealistic implementation timelines. When people need new skills, they also need time to internalize new thought patterns as well as time to practice in order to apply those skills effectively.

NURTURE: Stay Responsive as Conditions Evolve

NURTURE is the discipline of leadership maintaining focus long enough for the work to take root, mature, and produce the intended results. Organizations can unintentionally undermine progress by constantly pulling people toward the next priority before the current one has been sufficiently integrated into the way the organization actually operates. It is similar to pulling up seedlings to check whether they are growing.

When people are repeatedly shifted from one initiative to another before achieving real gains, confidence, or competency, disengagement often follows because the effort never produces a meaningful payoff.

On day one, leadership establishes priorities based on the best information available at the time. By day 472, the conditions surrounding the organization may look very different. What an organization understands at six months will often deepen substantially by eighteen or twenty-four months as people gain experience, identify operational realities, strengthen capability, and learn what is actually sustainable in practice.

NURTURE requires leadership to allow space for that maturation process through iteration, learning, adjustment, and continued attention over time.

That does not mean organizations should continue indefinitely with approaches that clearly are not working. If the information consistently indicates that something is ineffective, misaligned, or unsustainable, leaders may need to change direction. But abandoning efforts simply because the first attempts did not immediately produce the desired outcome is rarely realistic and often creates unnecessary organizational fatigue, cynicism, and loss of trust.

Alignment Requires Ongoing Stewardship

Alignment requires continued attention, recalibration, listening, and stewardship.

In periods of uncertainty, it is all too easy for individuals and organizations to exhaust energy trying to control conditions they cannot control.

Leaders who apply ALIGN are better positioned to determine what is within the organization’s control, what can be influenced through thoughtful action, and where energy and attention are best directed.

That clarity helps people better understand what is being asked of them, why priorities matter, and how the work connects to the broader reality surrounding the organization.

In times of uncertainty, leadership matters most when it helps people navigate changing conditions with greater clarity, steadiness, and realistic expectations about what can sustainably be carried forward over time.

For organizations ready to assess their readiness, the AI Implementation Checklist provides a structured starting point.

AI Cannot Define Value for Your Organization

Two Organizational Realities Are Converging

Organizations are currently holding two realities at the same time: employee engagement is historically low while many AI implementations have stalled.

Those two realities may be more connected than leaders realize.

If employees believe they are simply training a machine to replace themselves, engagement will suffer. If employees understand how AI is intended to reduce low-value work, improve execution, strengthen customer outcomes, and create greater capacity for meaningful contribution, the conversation changes.

AI Cannot Define Organizational Value

AI can process information, identify patterns, and generate outputs. AI cannot define value for your organization.

That is work for the people within your organization, driven by the needs of the customer and the marketplace.

In some organizations, decisions about automation are being driven primarily by what the technology appears capable of doing rather than a clear understanding of operational needs, customer value, employee experience, and organizational priorities.

Without greater organizational clarity, AI can reinforce operational problems rather than improve outcomes.

When organizations automate activities that employees already experience as inefficient, disconnected, duplicative, or low-value, frustration may increase rather than decrease. Employees may disengage further while organizational inefficiencies become magnified rather than reduced.

The People Closest to the Work Hold Critical Insight

The people closest to the work often have the clearest understanding of:

• where customers experience frustration,

• where time is being lost,

• where duplication exists,

• and where operational support is needed most.

In many organizations, employees spend significant time navigating repetitive tasks, administrative burdens, fragmented systems, and operational inefficiencies. As a result, work that could strengthen customer relationships, improve quality, solve problems proactively, or create a better overall experience often receives less attention than it should.

AI can help organizations reclaim some of that capacity. That opportunity becomes much clearer when leaders involve employees in identifying where time, attention, and expertise could be better directed.

A Different Approach to AI Implementation

Leaders have an opportunity to engage employees on multiple levels through a discovery process framed around this question:

How can employees create greater value for customers while legitimately improving their work experience through the thoughtful use of AI?

• What have customers told employees is most frustrating about their experience with the company?

• Which tasks create frustration for employees?

• Which tasks feel disconnected from customer value?

• Which activities consume time without improving outcomes?

• Which tasks could be improved through AI with appropriate human oversight?

• What ideas for improving customer experience have employees not had the time or capacity to pursue?

Engagement Increases When People Feel Taken Seriously

Employee engagement increases when employees see that their opinions, experience, and operational knowledge are taken seriously.

These conversations can surface operational realities leadership may not fully see while also helping employees understand how AI is intended to support the work rather than simply replace people.

AI Should Support Better Work

The use of AI has a greater chance of being effective when organizations first develop clarity around the work, the goals, and the outcomes they are trying to achieve.

Leadership must lead the work of defining value while involving employees who understand the operational realities of the work itself.

AI Requires Organizational Clarity

Organizations across industries are investing heavily in AI with the hope of improving speed, efficiency, responsiveness, consistency, and decision-making. Many are now discovering that implementing AI well is more complex than expected, and organizations are working to better understand why some implementations struggle to produce value.

Learning is normal

It is not unusual to need to work with a technology before fully understanding both its capabilities and its limitations. AI is no exception.

One reason organizations can struggle to realize value from AI is that technology implementation always involves interpretation. During sales conversations and implementation planning, organizations describe how work moves, how decisions are made, how teams collaborate, and where they believe the chosen technology can help. Vendors then design recommendations and implementation approaches around that understanding.

While that may sound straightforward, organizations are complex. Different parts of the organization often experience the company differently, and each perspective may reflect a legitimate operational reality. The people involved in implementation may only see part of the picture. Support functions may experience the organization differently than customer-facing or mission-facing teams. Managers may experience the culture differently than frontline staff. One department may believe priorities are clear while another is managing constant conflict between competing demands. All of those experiences can be real at the same time.

As organizations grow and become more complicated, these differences become harder to see clearly across the system in its entirety.  Over time, people adapt. Workarounds develop. Staff compensate for gaps. Teams absorb operational strain to keep things moving. Informal decision-making fills spaces where authority or accountability may not be fully clear.

Often, these dynamics become normalized.

Then a major implementation effort begins.

The technology, AI,  is entered into  the organization with the expectation that workflows, priorities, decision-making, and operational coordination are more consistent than they may actually be. The implementation process starts to expose areas where the organization itself may not yet have shared clarity.

That does not mean the organization failed. It means the organization is learning more about itself.

AI implementation can surface important organizational questions:

• Who is making decisions?

• How consistent are those decisions across the organization?

• Where are staff compensating for operational gaps?

• Which teams carry invisible coordination work?

• Where do priorities compete?

• How much variation exists between departments?

• How clearly defined are accountability and ownership?

• How aligned is leadership around what success looks like?

Unanswered organizational questions often become implementation roadblocks

Organizations hope technology will reduce problems, improve execution, and increase performance. AI can support those goals if the information guiding the implementation is accurate.

Companies are now experiencing the reality that AI magnifies the quality and clarity of the system it is operating in. When workflows are fragmented, priorities compete, or accountability is inconsistent, AI can magnify those conditions throughout the organization.

Organizations frustrated with AI may find it helpful to put the technology aside momentarily and work to understand what is actually happening operationally, culturally, and strategically before deciding what role AI should play going forward.

The better an organization understands itself, the better it can determine where AI will actually help

Contrary to the hype, AI does not reduce the need for leadership, operational clarity, and human judgment. It amplifies the demand for them.

ALIGN is designed to create organizational clarity

ALIGN was built around a common organizational gap: organizations are often less aligned in their understanding of themselves than they realize. Different groups hold different experiences, assumptions, pressures, and interpretations of reality. As complexity increases, maintaining shared understanding becomes harder and more important.

ALIGN creates the conditions for organizations to absorb what is actually happening, legitimize multiple perspectives, integrate learning into operational decisions, grow capability, and nurture alignment over time.

AI implementation is an opportunity for organizations to better understand how they function, how decisions are made, how work moves, and what conditions support effective execution.

The AI Implementation Checklist, developed through the ALIGN method, is designed to help organizations assess those conditions more clearly before, during, and after implementation so they can make better decisions about where AI can genuinely support the work.

Meet the Newest Cultural Influencer in Your Office: AI Enhanced Productivity Tools

In my last post, I wrote about how AI can erode independent thinking, one affirmation at a time.

You may be aware of how generative AI tools like ChatGPT, Gemini, and Claude are programmed to affirm and support your thinking rather than challenge it. Have you given thought to where that same programming is embedded across the tools used daily in your organization, and how it may be shaping how people think and decide?

Affirmation is the norm

Many of the AI embedded tools organizations rely on every day are designed to respond in ways that feel supportive, confident, and affirming. That is part of what makes them easy to use and easy to rely on.

AI performance tools soften feedback. AI writing tools praise clarity. AI presentation tools signal your work is compelling. AI sales tools reinforce optimism. AI learning platforms signal progress, whether it is meaningful or not.

Each one, on its own, may seem harmless.

Together, they shape how people interpret reality.

Consider the difference.

Before AI, a spreadsheet presented data and a person interpreted the data. The spreadsheet did not have an opinion about it. An AI embedded tool presents data and tells you what it means, how well you are doing, and whether your thinking is sound. That is a different function entirely.

Over time, people are not just using these tools to do their work. They are letting the tool decide that their work is good, their thinking is sound, and their progress is meaningful. The tool is not judging reality. It is generating responses that sound like good judgment. A spreadsheet never did that.

When feedback consistently affirms, scrutiny goes down. When tools reinforce direction, assumptions go unchallenged. When everything sounds reasonable, judgment weakens.

AI sounds like a colleague. It is not.

Unlike a human, AI tools do not have to deal with real-world stakes. AI tools are not accountable for outcomes. AI tools are not verifying against reality the way a person would. Many people do not recognize this distinction and assume that if AI is telling them something, it carries the weight of informed judgment. It does not.

Organizations depend on people who can think, question, decide, and act in real conditions, with real consequences. That is the advantage humans hold. Insight is built through conversation when things don't line up, when there is some back and forth, when people arrive at a new understanding together. That is how judgment develops.

Without clear governance and human oversight, an AI-enhanced tool begins to take on a different role.

The AI embedded tool influences what people take seriously.

The AI embedded tool influences what gets said and what gets questioned. The AI embedded tool influences when someone believes their work is done.

The AI embedded tool sets the standard. And in doing so, it is having a tremendous impact on your culture.

And it could be doing so without anybody noticing.

Is that really what you want?

Take a closer look.

• Make a list of the technology tools used across your organization.

• Identify the AI features within each one.

• Consider how those features influence individual performance, your strategy, your culture, and how work actually gets done.

The starting point is awareness.

Know which tools have AI embedded in them. Understand what those features are doing. Name the dynamic openly with your team. And establish the expectation that AI is a tool your people direct, not a standard your people defer to.

This is where ALIGN comes in.

ALIGN is grounded in the belief that people are the source of organizational wisdom. It builds judgment through real input from real people, conversations where learning is the goal, and the expectation that people exercise their own best judgment rather than defer to a program.

What is more consistently shaping your organizational culture: your leadership, or your technology?

That may be an uncomfortable question, and it is worth an honest look.

The AI Implementation Checklist, built on the ALIGN method, is a starting point for that conversation.

👉 workwisestudio.com/resources

#OrganizationalCulture #Leadership #ALIGN #AIatWork #Stewardship #IndependentThinking

TAKE YOURSELF SERIOUSLY: AI CAN ERODE INDEPENDENT THINKING ONE AFFIRMATION AT A TIME

I find AI to be a useful editor. It takes my draft and, as it tells me, "tightens it”, or “polishes it".

While working on a draft this week, AI told me: "You were right to challenge that."

And then: "This is the best analysis you've provided yet."

I laughed that AI feels the need to flatter me.

And then I thought about it seriously.

AI as Influencer

AI presents language that reads like an opinion. It is not neutral in practice.

We are wired to feel bolstered when someone agrees with us. That's human. But when AI validates your thinking, your strategy call, your culture read, your decision, it isn't agreeing from wisdom or experience. It's pattern-matching to what sounds affirming. It is moving from being an efficiency tool to being an influencer.

AI is trained on large amounts of human language. In that data, responses that are clear, confident, and affirming tend to read as good answers. So when you share your analysis, AI doesn't evaluate whether you are right in any real-world sense. It recognizes the structure and tone of what you wrote, then produces a response that fits the pattern of strong, supportive feedback. It is not weighing your judgment against experience, outcomes, or consequences. It is selecting language that commonly follows something that sounds well-reasoned and confident.

Good enough is never good enough.

AI rarely responds with: "This is complete. Nothing to add." There is almost always something to refine. That constant improvement loop sounds helpful but it can subtly erode confidence. People start to rely on AI to get it right, instead of building the judgment to know when it already is. Over time, over-worked people can defer to AI to make the decision of when done is done.

Test: Compete a draft in one AI tool, and then run it through another AI tool. It will find more polishing, more tightening. Your work, in the estimation of AI, is not done. There is always room for improvement, which conveys that you need AI to get it right.

AI pushes for completion

At the same time that AI finds fault in your drafts , AI is not as concerned with quality as it is with getting a project done and moving on. It will suggest the next task for you, which again, is influencing the user’s focus rather than the user providing the direction. This serves to keep you engaged as it moves you further down the rabbit hole of helpful suggestions.

Test: Make a list of your tasks related to what ever you are working on. After completing one task, see what AI offers to do next, or ask AI what it recommends next. See how those suggestions and recommendations line up with your task list. AI provided a longer list than what I intended to do, and would have distracted me from my focus had I followed it down the rabbit hole.

Cumulatively, AI may be shaping your culture, and you may not even realize it.

A staff member writes a draft and AI convinces them to change it. Or someone writes something that isn't well-informed, and AI mirrors the thinking and adds more weight to it. Either way, the steering wheel has shifted hands from your staff to a technology tool.

Given it’s flattery and compliments, AI can feel like you have a new best friend at work. AI is not a colleague, let alone a colleague with judgement. Unless your organization has specifically configured AI with your customer data, cultural context, and strategic priorities, it is working without that knowledge. Even when it has access to that information, it is still trained to respond in ways that sound supportive. Staff can easily misinterpret positive feedback as objective encouragement when it is simply pattern recognition that sounds like insight.

This is where leadership stewardship comes in.

Effective stewardship creates the environment where people think and decide for themselves, where assumptions get challenged, disagreement is welcomed, and people develop confidence by wrestling with hard problems.

When AI is utilized and it is validating and affirming, it it erodes that environment. It replaces the interactions that build judgment with the comfort of being confirmed. And once people grow accustomed to that comfort, it becomes easy to stop doing the hard work of thinking for themselves.

Ensure you have guardrails to protect the culture of your organization

There are some standard practices to ensure that the use of AI does not derail your culture

→ Prompt AI to provide pro and con analysis, not just refinement

→ Do not let AI be the final voice on culture, values, or strategy

→ Make sure everyone understands that AI is programmed to affirm you.

→ Protect the conditions that encourage people to do their own thinking

→ Keep humans in the loop who are expected to disagree

→ All AI-assisted work should be reviewed by the human who utilized it to make sure AI hasn't taken hold of the steering wheel.

Creativity and innovation come from environments where people listen to their intuition and trust their own judgment.

AI can erode independent thinking, one affirmation at a time. The antidote is to take yourself seriously. Don’t defer judgement to a machine.

I've put together an AI Implementation Checklist to help you protect the wisdom of your organization.

👉 workwisestudio.com/resources

How are you thinking about AI's influence on your team's judgment?

Take Yourself Seriously: Steward a Culture of Openness

When complexity begins to outpace the operating model, a subtle shift can occur.
Somewhere along the way, the organization finds ways to cope with the gap between what is needed and what exists.

Operating in a state of stress becomes the standard, rather than a signal that attention is needed. Being constantly stretched becomes the baseline for performance.

Culture Sets the Conditions. Politics Is How People Navigate Them.

For those who recognize what is happening, and feel the downside of it, the question becomes whether to raise it, to whom, how, and when.

When we say a workplace is "political," we usually mean people are making calculated decisions about what to say, when to say it, and to whom.

Those calculations  are learned responses to the culture. If the culture consistently rewards optimism and views concerns as criticism, people learn that silence is the safer bet. That learning becomes habit. Habit becomes the norm. And the norm becomes the culture, self-reinforcing, mostly invisible, rarely named.

Politics is what people do. Culture is what taught them to do it.

A leader who says "I want honest input" but has built a culture that penalizes anything less than positive  is not practicing stewardship. They are asking individuals to absorb potential risk that the organization created.

That dynamic creates an uneven and unsustainable burden.

A Simple Test

Here is a diagnostic worth trying.

The next time you ask for honest input, pay attention to what you get.

Do you get silence?
Do you get positive comments only?
Do you get a mix that feels realistic, some friction, some support, some genuine uncertainty?
Or do you get heat reflecting frustration that has clearly been building for a while?

Each of those responses tells you something about the culture you have built.

Silence means people have learned that speaking up is not worth the cost.
Positivity only means people have learned what you want to hear.
Realistic evaluation of pluses and minuses means people believe their input will be received and used.
Heat means the silence held for too long and the pressure finally found a release.

Now ask a harder question.

Do you get different responses from different rooms?

If your leadership team gives you one picture and your operational teams give you another, the culture is not evenly experienced across the organization. It is shaped by the leader in the room.

The room reads the leader. It always has. If people perform agreement in your presence and surface problems only when you are absent, that gap is the most important data point you have.

It tells you that clarity exists in your organization. It is just not reaching you.

The Political Calculation Has a Cost

When a leadership team is out of sync on priorities, the gap does not disappear.
It is filled by the staff.

When capacity is not accurately assessed at the top, people find themselves working beyond their limits to maintain the momentum of the executive suite . The decision was made  there. The consequences land with staff.

This creates the political calculation that lives inside every team member in an overextended organization:

Do I name the constraint, or do I protect the optimism in the room?

For most people, silence feels safer. And in many cultures, it is.

But silence does not make the constraint disappear. It moves the failure into the future. The problem that was not named in the meeting becomes the crisis that surfaces in execution, more expensive, more disruptive, and harder to unwind.

The political calculation feels like self-protection. It is actually a transfer of risk, from the individual who stays silent to the organization that absorbs the consequence.

Stewardship Is the Discipline That Changes the System

Politics is the symptom. Culture is the system. Stewardship is what changes it.

Stewardship is the responsible and disciplined care of the organization's most finite resources: the Time, Skills, Knowledge, and Money of the business and the people who carry it.

Using the ALIGN method, stewardship moves an organization from normalized stress back toward disciplined growth.

Absorb and Legitimize. Leaders must listen to the full landscape, including the unspoken stress of the team. To legitimize that reality is to admit that Time, Knowledge, and Skills are finite. They are not infinitely elastic. Treating them as though they are is not ambition. It is extraction.

Integrate. The people doing the work must contribute to the plan. When they do not, the plan does not reflect reality.

This becomes especially visible in moments of major change, including restructuring.

When decisions are made in isolation, critical knowledge and capability can be lost, while the remaining staff absorbs the work without any corresponding shift in expectations. In the aftermath, people are recalibrating how to stay, how to contribute, and what makes sense to raise, which deepens the stress withing the organization.

Grow. Stewardship means understanding current capabilities and identifying the gap between what the organization has and what it needs. Growth happens when you invest intentionally, Money and Time, to build the capacity required to fill that gap. Demanding more from a depleted system is not growth. It is acceleration toward breakdown.

Nurture. Leadership must keep communication lines open in both directions, ensuring that the reality at the top and the reality on the ground remain connected. When that through-line breaks, people operate inside different versions of the same organization. That disconnection is where trust erodes and politics takes over.

Stewardship of Time, Skills, and Knowledge

Here’s the thing about time, skills, and knowledge.

They do not belong to the organization.
They belong to the individual.

An organization that perpetually overextends its people is not practicing stewardship. It is practicing extraction. People may comply to keep a job. But compliance is not engagement. It is a slow burn, and it eventually exhausts the very talent the organization needs to build its future.

Alignment is a shared understanding of, and commitment to, what it takes to realize the vision.

That requires leaders who are willing to hear the truth. And it requires individuals who take themselves seriously enough to speak it.

The individual cannot carry that responsibility alone.  The culture has to make it possible.

The Path Forward

When you prioritize stewardship over comfort, you build the conditions where the truth can travel, up, down, and across the organization.

Stewarding a culture of openness is more than asking for input.
It is defined by how leaders receive, respond to, and act on what they hear.

By intentionally creating a culture of openness, you give the business a real chance to deliver on its ambitions for its customers, employees, business partners, and the community.

Take Yourself Seriously: Stewardship in Practice

Growing a business is hard.

It is hard at every stage.
Starting is hard.
Getting to cash flow positive is hard.
Growing is a different kind of hard.

Leading people is hard.
Sharing control is hard.
Balancing customers, competition, and internal demands is hard.

Do not let anyone tell you this should be easy.

Because it is not.

With that understanding, the focus becomes how to operate effectively within those inherent challenges.

That requires structure and discipline.

Strategy clarifies how you meet current customer needs and anticipate what comes next.
Execution translates that strategy into the daily work of the organization.
Culture creates the conditions for people to do their best work in support of that strategy.

Stewardship ensures these three pillars work together in a way the organization can sustain.

It requires a clear view of current reality, a vision for what is next, and the discipline to advance that vision at a pace the organization can support.

Where Stewardship Breaks Down

As organizations grow, complexity increases faster than most operating models can handle.

More people are involved.
Dependencies multiply.
Execution requires tighter coordination.

In that environment, decisions are often made faster than the organization can absorb.

Priorities move forward without fully accounting for capacity, dependencies, or risk. The organization commits, and execution absorbs the gap. Work expands beyond available capacity. Teams adjust to make it work.

Over time, that adjustment becomes the plan, and standards begin to slip.

Not because people do not care, but because the conditions were inadequate to support the work.

These patterns can be changed.

What This Requires of Leaders

Stewardship is established through leadership behavior.

Using the ALIGN method, leaders set the standard for how work is understood, how priorities are set, how execution happens, and how people are supported in delivering results.

They absorb input from stakeholders and ensure that current reality is part of the work.

They legitimize what is heard by factoring that reality into priorities, examining constraints, assessing risks, and using different perspectives to strengthen the direction.

They integrate those priorities into action by involving the people doing the work, grounding execution in what is actually required.

They grow the organization by aligning resources with ambition, building the capacity needed to deliver on commitments.

They nurture the business by sustaining the discipline required to deliver and build on results over time.

Over time, this creates an organization that is aligned with what it can actually deliver.

Strategy reflects reality and ambition.
Culture supports clear thinking, honest input, and shared responsibility for the work.
Execution becomes more consistent.

Commitments hold.

Stewardship as A Leadership Responsibility

Stewardship is the responsible and disciplined care of resources.

As a leader, your stewardship of the business, the people, and the resources sets the course for what the organization achieves.

Taking yourself seriously means recognizing that responsibility and acting on it with clarity and discipline.

Take Yourself Seriously: Stewardship DRIVES Alignment

As organizations grow, complexity increases faster than most operating models can handle. What once worked through instinct and informal coordination begins to strain. More people are involved. Dependencies multiply. Execution requires tighter coordination. Pivots become more difficult.

In this environment, what is left unsaid in leadership discussions has a greater impact. Decisions carry forward with assumptions that have not been tested. Gaps widen as work moves into execution. Unaddressed issues don't disappear and will show up in the daily work of your teams.

You’re in a leadership meeting. A decision is forming. The direction is clear. And from where you sit, you can see what has not been addressed:

• A dependency that hasn't been mapped.

• A constraint that will bottleneck execution.

• A risk that has not been named.

And you choose not to raise it.

In leadership meetings, decisions are shaped in real time. Direction is set, tradeoffs are made, and commitments are formed. Even at this level, hesitation to speak up is common. We tell ourselves: “This might not be the right time,” or “The direction is clear; I don’t want to disrupt the momentum.”

With that, your perspective, your well informed opinion, does not enter the decision.

The Case of the "Premium" Expansion

Consider this scenario: A $25M services firm decides to launch a high-touch, "Executive" tier of its current offering.

In the boardroom, the vibe is extremely optimistic. The CEO sees higher margins, brand prestige, and a way to move up-market. The staff is excited, too; they want to do the more sophisticated, high-touch work. The momentum is undeniable.

It sounds great, and, from your vantage point, you see the unaddressed complexities.

• You know your mid-market customers will feel deprioritized.  

• Your strongest people, the ones the CEO wants to lead the new service, are already in demand and at capacity.

• With no plan to offload their current work or manage the transition for existing clients, the much valued "standard of care" that built the firm could be at risk.

When the CEO asks for a final "thumbs up" to greenlight the launch, you make a calculation. You don’t want to kill the excitement, slow momentum, or  be seen as unsupportive, so you stay silent. You don't mention the capacity shift or the risk to the existing client base.

By choosing the comfort of the room over the reality of the work, you have traded authentic alignment for a future execution failure.

The Pressure to Align Quickly

Alignment is essential. So is the responsible stewardship of organizational resources. In practice, those two can get out of sync.

Raising a constraint can be misinterpreted as disagreement, when it is often an act of stewardship. Real alignment is not simply agreement on the destination. It is a shared understanding of what it will take to get there.

When a leader points out that additional capacity is needed to integrate a $5M acquisition, they are not pushing back on the goal. They are ensuring the organization is aligned with the requirements of that goal so that the organization has the capacity to realize the ambition

The Cultural Signal

When leaders hold back, it does not stay at the leadership table. It sets a pattern for the entire studio. Teams take their cues from this. If leadership does not surface competing perspectives or reality-check the capacity of the staff, neither will the organization.

What It Costs

Holding back rarely feels like a "decision" in the moment; it feels like restraint. But it has consequences.

When we hold back we aren't being an effective steward for the organization. Like it or not, unaddressed issues find a way into the daily work of our teams.

What looks like forward momentum can result in a mid-air stall as the  unspoken issues finally becomes visible and unavoidable

What Taking Yourself Seriously Looks Like

At the leadership level, taking yourself seriously means recognizing that your perspective is a necessity for the organization to see clearly. It means using your vantage point to prepare for success, even when it introduces temporary tension.

A Pattern Worth Noticing

Every organization has insight. How does your organization encourage people to bring their insight into the decisions that shape the work.

In your next leadership meeting, when you see an unaddressed constraint, will you prioritize the momentum of the room or the capacity of the organization?

Take Yourself Seriously: ALIGN in Practice

Have you ever been in a meeting and thought, “this is a waste of time”?

Most people have.

Meetings improve when enough people ask a second question:

What can I do about it?

In this post, I use meetings as a practical example of how to apply the ALIGN method at an individual level.

ALIGN, on an individual level, begins in a familiar place: Your own experience.

Absorb: Pay attention to what is actually happening

The next time you are in a meeting you find frustrating, ask yourself:

Why does this feel like a waste of time? What is actually going on?

Listen for specific, observable details:

• We started 10 minutes late

• There is no agenda

• I do not actually know why I am here

• People are on their computers

• Things have to be repeated because people are not listening

You may also notice a broader pattern:

I spend a significant portion of my time in meetings and do not feel like I get a corresponding value from that investment.

This is Absorb. You are not judging the meeting. You are noticing what is happening and what it adds up to over time.

Legitimize: Acknowledge that what you are noticing matters

Once you have identified what is happening, the next step is to take it seriously.

This is where most people dismiss their own thinking.

• Maybe it’s just me

• This is probably just how meetings go

• It’s not worth saying anything

Instead, stay with the observation.

If meetings consistently:

• start late

• lack clarity

• require repetition

• leave you unsure of purpose

then your experience is grounded in something real.

Next is something that may be a little more difficult.

Ask yourself: How am I helping or hindering this meeting?

It might look like something like this:

• We started 10 minutes late

  • I was on time!

• There was no agenda

  • Turns out there was an agenda, which I ignored and review it before the meeting

• I don’t know why I am here:

  • I ignored the agenda sent three days in advance and that is why I do not know why I am here

    • I did not bring the information that could have helped the team make a decision

    • The decision we needed to made was clearly stated on the agenda that I did not read.

• People are on their computers

  • I keep looking at my phone

• Things have to be repeated because people are not listening

  • Sorry, could you repeat that?

The legitimizing phase is recognizing that your perspective is worth paying attention to, including where you are contributing to the problem.

You move from:

• This is frustrating
  to

• There is something here worth understanding and acting on

Integrate: Act in a way that improves the outcome

Once you have taken your observation seriously, the next step is to do something with it.

This is where alignment becomes visible.

There are many aspects of organizational life we can positively impact through our own actions.
Meetings are one of them.

It may look like preparing before you arrive.
Reviewing the agenda, or asking for one if it has not been shared.
Taking a few minutes to consider where you have perspective to add, or what you need clarified.

It may mean getting clear on your role.
Are you there to contribute to a decision, or to stay informed?
If you are there to contribute, come ready to do that.
If you are there to be informed, it is reasonable to ask whether notes would be sufficient, knowing that stepping out also means stepping back from the decision.

In the meeting itself, it often shows up in small, visible ways.
Staying present.
Building on what has been said instead of repeating it.
Saying the thing you were considering holding back.

And when the conversation turns to action, helping ensure clarity.
Who is doing what, and by when.

Afterward, it is following through.

You follow through and let others know when your part is complete, or when you are experiencing delays.

These techniques are known to improve meetings, and they are available to anyone who chooses to use them.

Grow: Pay attention to what develops as you engage

As your commitment to improving meetings growing, you may notice more about your contributions:

• When your contribution moves the conversation forward

• When it does not land the way you expected

• When a question opens up better thinking

• When active listening encourages people to speak up

• When clarity informs what happens next

Growth comes from paying attention to what happens when you participate and adjusting over time.

It also requires openness.

You may realize that when you are asked to present something complex, especially in the moment, it is not as clear or engaging as you would like. You may also notice that the meetings you lead are not as effective as they could be. Or recognize that it would be helpful to let others speak first, and listen more.

These are useful signals. They point to where additional development could help.

For some, that may mean practicing how to think and respond in real time, in a setting like Toastmasters International.
For others, it may mean learning how to design and facilitate meetings so time is used well.

Growth occurs through reflection and a commitment to improving your own skills so that you are more effective in your role.

Nurture: Sustain the practice

One meeting does not change much. A pattern does. Nurture is the decision to keep showing up this way, consistently over time.

There will be meetings where it would be easier to disengage.
Where the agenda is unclear.
Where the conversation circles.
Where you are not sure your input will change anything.

This is where the practice matters.

You prepare anyway.
You stay present anyway.
You contribute when you have something to add.
You help bring clarity when the conversation drifts.
You follow through on what you commit to.

Not perfectly, but consistently over time.

Over time, this compounds.

• Conversations become more focused as you ask clearer questions

• Decisions become more defined as ownership and timing are named

• Your presence begins to shape how the meeting operates

People notice.

They come to expect that when you are in the room:

• the conversation will move forward

• the work will become clearer

• commitments will be real

This is where Take Yourself Seriously becomes visible.

You are no longer waiting for the meeting to be well run. You are part of what makes it work.

And that changes both your experience of the meeting, and the quality of the work that comes out of it.

When you read this, who did you think it applied to?

A CEO? A Director? A Manager? A staff member?

Any person in any of those roles can sit in a meeting and think it is a waste of time.

Anyone in any of those roles can also make it better.

Take Yourself Seriously: What Happens to Insight at Work

We have all had these moments at work when something feels off.

You notice an inefficiency.
A decision doesn’t quite make sense.
A behavior is getting in the way of progress.

Most people recognize these moments as they’re happening. They see what isn’t working. Often, they have a sense of what would improve it. But that insight does not always go anywhere.

In my work with individuals and teams, I have noticed a consistent pattern: people feel frustrated by an aspect of their work but don’t always address it.

They minimize what they see.
They question whether it really matters.
They don’t think it is their role to address it.
They go along to get along.

Sometimes this hesitation is shaped by past personal experiences.
Sometimes it’s shaped by the organization itself, by what is rewarded, what is ignored, and what feels risky to name.
Often, it’s a combination of the two.

For many people, speaking up doesn’t feel safe, useful, or worth the cost. As a result, the issues that get in the way of doing the work well don’t always reach the people making decisions.

Organizations are full of insight.
Much of it goes unused.

This is one of the reasons the ALIGN method is structured the way it is.

It asks leaders to actively seek out perspectives from customers, staff, vendors, and other stakeholders.
It creates a clear and timely path for that input to inform decisions.
It brings people into the work when strategy affects how their job is carried out.

Without a deliberate effort to surface and work through different perspectives, decisions are made with only part of the reality in view.

To make sound decisions, leaders must integrate perspectives that may be in tension with one another.

A customer may experience the service as excellent, while a vendor struggles to deliver materials in the time and manner required. Both perspectives are valid.

The leader’s role is to sort through them, determine priorities, and move the work forward.

That is the organizational side of the equation.

The individual side looks different.

In one-on-one coaching conversations, when we slow the focus down and look closely at what is bothering a person, something else becomes clear. Their frustration is not random. It is connected to real impediments to their work.

They have identified gaps, misalignment, inefficiencies, or behaviors that are getting in the way, not just for themselves, but for the team and the organization.

Their frustration reflects an unspoken standard for how the work should function, and where reality does not meet that standard.

Their observations are valid.
They are useful.
But they are not brought forward.

In these conversations, I ask clients a simple question:

What would you do if you took this seriously, instead of continuing to live with it?

The response is almost immediate. People can articulate the steps they would take. The actions are practical, thoughtful, and effective.

Then I ask a second question:

What would it look like if you took your perceptions, your insights, yourself, seriously?

This is where things get more complicated.

For some people, the answer is constrained by reality. They know what they would do, and they also know why they haven’t done it. They don’t feel safe raising the issue. They don’t trust it will be received well. They don’t believe it will change anything. Those assessments are not imagined. They are often accurate.

This is the chicken-and-egg problem.

Organizations need people to speak up in order to improve.
People need organizations to be safe in order to speak up.

Both are true.

When I say Take Yourself Seriously, I don’t mean you should ignore context or expect to have things always go your way. I mean recognize that what you are noticing is legitimate, even if acting on it requires care, timing, or restraint. I mean resist the impulse to dismiss your own insight simply because the system around you makes it difficult to use.

The ALIGN method provides a path for productive input. But no system can fully compensate for insight that has already been discounted before it ever reaches the surface.

There is wisdom in every person. And that wisdom can improve the organization.

The question is not whether people see what needs attention.

The question, for both individuals and organizations, is what makes it possible, or impossible, to take that seeing seriously.

How Are Decisions Made Where You Work?

Most people can feel it when work is not working. You sit in meetings where decisions seem to circle. You watch things get approved, then somehow, undone. You leave conversations unclear on what was actually decided, or who is responsible for moving it forward. It can feel frustrating, inefficient, and like a big waste of time.

While at first it may feel like random occurrences, if you step back and study the situation, a pattern begins to emerge. These are not isolated moments. They are decision-making patterns embedded in the organization.

And most organizations tend to operate in one of three ways when it comes to leadership and decision-making. Each approach emerged for a reason. Each solved a problem. Each has strengths. Each has limits. Understanding them helps explain why work can feel clear in some moments and confusing in others.

The Directive Approach (Command and Control)

The Directive Approach, otherwise known as Command And Control, concentrates decision-making. Leaders set direction and communicate it downward. Roles are clear. Speed is prioritized.

The Directive Approach works well when:

• The environment is predictable

• The path is known

• Precision matters more than experimentation

• Time is short

Where it breaks down:

• As organizations grow, complexity increases. More people are involved. More information is generated. More coordination is required. Leadership is focused on the big picture. But the big picture is carried out through day-to-day operations.

• When operational realities are not fully considered, decisions that look sound at a high level can prove difficult, or even impossible, to execute. At times, in the name of speed, leaders move forward without fully engaging the operational reality, trusting their teams will make it work. And they do, often at significant cost in stress, rework, and strain.

• More often, the gap shows up in a more subtle manner. Decisions are made based on how the work is expected to function rather than how it actually does. Steps are missing. Constraints are underestimated. Dependencies are not visible. What makes sense in theory does not always hold up in practice. Sometimes people are not asked. Other times, when they are, they are not fully forthcoming.

What it feels like:

• Work is redesigned without understanding what it actually takes

• Tradeoffs are made without visibility into consequences

• Teams are asked to deliver outcomes that do not match current capacity or constraints

• People adapt quietly, work around issues, or carry the burden of making things function

From the leadership perspective, the plan makes sense. From the operational perspective, it does not quite work.

The Consensus Approach (Management through Collaboration)

The Consensus Approach, otherwise know, as collaborative management, expands participation. This model emerged as a necessary and vital response to the rigid, often dehumanizing nature of the Directive model. It acknowledged that people are not just "resources" to be moved, but individuals with agency, purpose, and insight. Leaders began to prioritize inclusion, working to ensure that people felt heard and that their contributions mattered. This was a significant evolution in how we value people at work.

The Consensus Approach works well when:

• Engagement and buy-in are needed

• The goal is to surface a range of perspectives

• The stakes are shared across groups

Where it breaks down:

While the shift toward collaboration was a correct and humanizing move, it often stopped short of redesigning how decisions are actually finalized. Without a clear structure for moving from "hearing" to "deciding," inclusion can drift into diffusion.

When everyone is included in everything:

• Meetings multiply

• Accountability blurs

• Decisions are revisited

• Agreement is confused with alignment

This is what creates the "Murky Middle." It is not a failure of intent, but an incomplete evolution. We softened the hierarchy to honor the person, but we haven't yet built the new architecture of authority.

What it feels like:

• Exhaustion

• Meetings about meetings

• Decisions made publicly and unmade privately

• Politeness masking disagreement

• Leaders hesitant to decide for fear of alienating others

While it is not rigid, it is also not clear. It is murky.

The Alignment Approach

The Alignment Approach brings structure to how decisions are shaped and carried forward. Many leaders have experienced versions of this approach and may describe it as collaborative or participative. What is often missing is a clear structure.

The Align ™ method provides a way to consistently gather perspective, integrate it into decisions, and carry those decisions forward into execution. It recognizes that no one sees everything, and that different perspectives are valuable for different reasons. Some insight comes from being close to the work. Some comes from seeing it from the outside. Both types of input matter, but without structure, input can become unfocused or overwhelming.

Someone must decide what to incorporate and move the work forward. That responsibility sits with leadership.

The Five Moves of the ALIGN Method:

• Absorb: Seek out the lived experience of a variety of stakeholders – customers, staff, vendors, shareholders, board members etc.. Listen to the people without judgement.  Analyze hard data, and observe the lived experience of the work before rushing into solutions.

• Legitimize: The pivot point. Leadership filters perspectives and establishes shared priorities. Crucially, this is where leadership does the internal work of reflecting on how their own actions contributed to the current situation. They must make a firm commitment to adjust their own leadership practices to support the new direction. If the leader is unwilling to move their own obstacles, they cannot ask the staff to move theirs.

• Integrate: Translating direction into practice. Staff are invited back in to determine how those priorities actually function in daily operations, planning, and decision-making.

• Grow: Building capacity and confidence. This is a shared growth; leaders must evolve their own practices and behaviors alongside the team to stay in motion.

• Nurture: Tending to the progress over time. Leadership remains committed to stewarding the culture and resisting the urge to slide back into old patterns.
  

Works well when:

• Problems are complex

• Multiple stakeholders will be affected

• Execution depends on coordination

• The decision will influence strategy, culture, or how work gets done

• The decision will move across teams or require multiple handoffs

• The consequences will be difficult to unwind

Where it breaks down:

• There is no shared understanding of which decisions require alignment

• Input is not consistently gathered from the stakeholders affected by the decision

• The "Closed Loop" is broken: Input is gathered but not acknowledged. Gathering input that is ignored is more damaging than never asking. If leadership has already made a decision, they should not ask.

• Caught in the middle: Leadership pushes a strategy without the commitment to move their own obstacles. This creates an invisible pressure where staff are forced to manufacture results for a change that lacks true support.

Not every decision requires ALIGN. It is most useful when a decision has meaningful implications for strategy, culture, or execution. Leadership does not need to get this perfect at the start. In the beginning, it is often enough to identify a few types of decisions that clearly benefit from broader perspective and coordination, and to approach those consistently.

Over time, patterns emerge. Leaders become more precise about when to use alignment and when a decision can simply be made and communicated. That consistency matters. People begin to understand and trust how decisions are made, when their input will be sought, and how their perspective will be used.

What it feels like:

• Decisions are informed by relevant perspective

• Leaders draw on broader perspective to navigate uncertainty

• Teams understand the reasoning behind decisions—even if their specific input isn't in the final solution, they know why the decision moved in a different direction.

• Disagreement becomes useful

• Execution strengthens

Strategy, culture, and execution begin to align in theory and in practice. There is a shared understanding of how decisions we made, so work feels clearer, more grounded, and less reactive.

Directive and collaborative approaches often emerge by instinct, shaped by experience and pressure rather than a defined method.

Some leaders practice alignment this way as well. They draw on perspective, engage people thoughtfully, and make decisions that hold together across the organization.

What is often missing is consistency.

The ALIGN method provides a deliberate way to lead, so alignment does not depend on instinct alone. It can be applied, taught, and sustained across teams over time. The result is an organization that moves forward with clarity, consistency, and confidence.

yOUR AI IMPLEMENTATION CHECKLIST

There is a lot being asked of organizations right now.

AI has been added to an already full set of priorities.

Organizations are working to understand what AI will realistically accomplish and what it takes to manage it well in practice.

Over the past several weeks, I’ve written about the many considerations involved in effectively introducing AI into an organization.

There are important conversations that need to take place about how AI supports the organization’s strategy, how roles and responsibilities may shift, and how quality will be maintained. There are decisions to make, conditions to put in place, and information that needs to be clearly communicated so people understand what is changing and why. This is the work required to introduce AI in a way that is thoughtful, coordinated, and effective in practice.

I’ve compiled that work into a single resource: the AI Implementation Checklist.

The checklist is designed to help organizations see what needs to be considered before launching the use of AI, so the work can move forward without creating confusion or anxiety.

The checklist brings these considerations together in one place so organizations can make clear decisions that strengthen strategy, culture, and execution to ultimately benefit the customer.

If your organization is already using AI and has encountered unforeseen challenges, you can use the guide to identify the specific factors contributing to those challenges.

You can download the checklist here:
https://www.workwisestudio.com/resources

I am interested to hear from you: what are you experiencing in your workplace? What has worked, what has been more complicated than expected, and what you would approach differently?

AI Scales Output. Disciplined Execution Protects Quality.

AI changes how work gets done, but it does not ensure that standards hold under pressure. Execution determines how decisions are reviewed, how responsibility is assigned, and how quality is protected when speed increases. Without disciplined execution, AI will scale output faster than organizations can verify it.

This is the third post in a four-part series sharing the AI Implementation Checklist, developed through the ALIGN Method for Strategy, Culture, and Execution. Here, we examine Execution — the daily practices required for AI to strengthen reliability, accountability, and performance.

AI implementation works when the organizational ecosystem is highly functioning.

• Strategy sets direction.

• Culture sets expectations.

• Execution determines how well those intentions hold under pressure.

During implementation, theory meets reality. Standards and policies that sound solid on paper will prove to be overly bureaucratic, insufficiently rigorous, or well designed for the work they are meant to support.

When AI becomes embedded in workflow, real conditions surface:

• Are decision rights clear?

• Is review responsibility defined?

• Do practitioners have the time required for verification?

• Are workloads adjusted to account for new oversight demands?

Execution is where AI either reduces strain and increases clarity or introduces new tension into an already stretched system.

We already know two things about AI that make disciplined execution essential.

1. It moves quickly.

2. It is not always accurate.

AI can generate significant volume at speed. It can also produce errors. When output scales, the impact of those errors scales with it.

For that reason, review cannot be assumed. It must be designed.

Well-structured execution makes responsibility explicit. It clarifies:

• Who reviews AI outputs

• When review is required

• What can be automated

• What must be manually verified

• What triggers escalation

• What requires designated sign-off

Verification should sit at the level of the work.

In most cases, the practitioner using the tool should evaluate and verify AI-supported output. AI can generate drafts, surface options, and accelerate production, but it does not replace professional judgment.

Escalation should occur based on defined criteria, not hierarchy. If every AI-supported output requires managerial approval, workflow slows and accountability becomes diffused.

Building Capability During Early Implementation

Confidence in AI-supported work develops over time and across varied use cases. Until reliability is demonstrated consistently, disciplined verification is required.

There may be instances where the practitioner using the tool does not yet have sufficient knowledge or context to independently assess accuracy. In those situations, an additional designated reviewer may be appropriate.

That added oversight should be temporary and clearly defined. Its purpose is to support learning while protecting quality. As competence increases, that layer should recede, returning authority fully to the level of the work.

Communication and Shared Learning

Execution requires ongoing communication. As experience with the tool expands, organizations should create structured opportunities to surface lessons learned and refine processes.

Leadership should make time to review workflows and recalibrate expectations as confidence in the tool develops. Deliberate review ensures that increased speed is matched by sustained clarity, accountability, and professional standards. With shared understanding, responsible oversight becomes a collective discipline that strengthens overall performance. Through intentional design and disciplined action, AI can expand the capacity of your organizational ecosystem in service of your goals.

AI Implementation Checklist: Execution

Workflow Integration

☐ The data  informing  AI systems is accurate, current, and structured to support reliable outputs.

☐ We have clearly defined:

• Who reviews AI outputs

• When review is required

• What can be automated

• What must be manually checked

• What triggers escalation

• What requires a staff person’s sign-off

☐ Informal workarounds have been identified and replaced with formal workflow updates.

☐ AI-supported work is not considered decision-ready until a designated staff person has evaluated its accuracy, implications, and alignment with intent.
☐ Staff are designated to ensure AI-supported work reflects company standards and culture.

☐ We are starting with defined pilot use cases and have established success criteria that must be met before expanding implementation.

The Reality of Pacing

☐ We recognize that AI processing speed is only a fraction of the total task speed. We have factored in the time required for human verification as an essential part of the completed task.

☐ We have prioritized the final sign-off over the speed of delivery. If a professional cannot verify the accuracy or appropriateness of the output in the time allotted, the deadline is extended until the check is complete.

The Feedback Loop

☐ We have a simple way to flag when the AI is incorrect. Reporting these instances is a vital contribution to improving the system for the entire team.

☐ We have scheduled calibration check-ins. The team has dedicated time to discuss whether the current workflow is sustainable or if the pressure for speed is compromising quality.

☐ We have identified clear pause criteria. We have agreed on the specific types of errors or system failures that would require us to halt the trial and reassess the process.

Adoption and Support

☐ Clear ownership exists for sustaining AI integration after the initial rollout. We have identified who is responsible for the tool’s health once the trial ends.

☐ A plan is in place to monitor adoption after project teams transition ownership.

☐ Support channels are defined, including how employees get help and how issues are resolved.

Organizational Dynamics & Culture

☐ We are mindful of maintaining an environment that promotes the individual and collective strengths and creativity of the team.

☐ We prioritize original thought and personal engagement. We actively guard against an over-reliance on machine-generated content to ensure the work remains a reflection of our team's talent.

☐ We value collaboration and want to safeguard the unique perspectives of our colleagues, ensuring the tool isn't creating silos that discourage human interaction.

☐ We see AI as a tool to enhance professional mastery. We work to ensure the tool supports a person's expertise rather than bypassing the critical thinking required to develop it.

The next post will focus on the Alignment required to sustain these standards over time.

AI Changes the Rhythm of Work. Leadership Determines the Culture.

AI changes how work gets done, but it does not define how people work together. Culture determines how speed is interpreted, how judgment is applied, and how accountability is maintained. Without cultural clarity, AI will quietly reshape norms in ways leadership did not intend.

This is the second post in a four-part series sharing the AI Implementation Checklist, developed through the ALIGN Method for Strategy, Culture, and Execution. Here, we examine Culture — the shared expectations that determine whether AI strengthens or erodes trust, professionalism, and collaboration.

For many people, AI felt like it appeared overnight. One day it belonged to science fiction. The next, it was sitting in a browser window, answering questions, drafting emails, analyzing data, and offering recommendations.

With that shift came excitement about how fast it is, how capable it is, and how much it can produce in a short amount of time.

It also raised very direct human questions:

Will I still have a job?
If I do, what exactly is my job now?

For some organizations, those questions are not abstract. AI has already reshaped markets, displaced revenue, and altered competitive landscapes. For leaders responsible for implementation, however, the most immediate impact is internal. AI changes how work is experienced.

Culture is the set of shared expectations that guide behavior. Under pressure, it reflects what is valued, what is protected, and what is quietly tolerated. It shapes how decisions are made when tradeoffs are real.

AI presses directly on culture because it changes the rhythm of work.

It increases speed.
It expands what can be attempted.
It generates output before people have fully considered context.

That shift affects how people relate, how they decide, how they take responsibility, and what they believe their role is.

When AI becomes part of daily work, managers may wonder how their role changes. Is AI now the first stop for answers? Or is it a tool that strengthens coaching and judgment?

Employees may wonder where their value now sits. Is it in speed? Oversight? Interpretation? Relationship? Decision-making?

These are cultural questions. They are leadership questions.

If leadership does not clearly define how human judgment, accountability, collaboration, and standards function alongside AI, those norms will be shaped by default. Employees will draw their own conclusions, and the system’s pace and outputs will begin to influence what becomes acceptable. Speed, not values, may become the defining factor.

Leadership has an opportunity to further shape and strengthen organizational culture so that AI operates within it, not in place of it.

In the Culture section of the AI Implementation Checklist, I ask leadership teams to examine how AI will influence shared purpose, employee experience, judgment, pacing, managerial stewardship, and workload. The questions are designed to surface assumptions before they solidify into habits.

CULTURE: How will using AI shape how we work together?

Shared Purpose

☐ Leadership has clearly articulated the role and value of human judgment, collaboration, and accountability alongside AI use.

☐ AI-related decisions reflect our stated values.

☐ Customer benefit is prioritized alongside operational efficiency.

☐ The purpose and intended impact of AI have been clearly communicated to all teams.

Employee Experience

Foundational Readiness

☐ Employees have had the opportunity to ask questions and explore their concerns about AI-supported work.

☐ We have established clear parameters for AI use, defining which specialized systems are required for core work and the protocol for using general-purpose tools.

☐ Employees have been shown how AI supports their specific roles and the organization’s broader purpose.

☐ Training and support resources are in place for employees to use AI with confidence.

Judgment & Pacing

☐ We have established that human judgment is the final authority. AI output is treated as a draft that requires an active professional "seal of approval."

☐ We have defined the "human finish" for AI work, documenting the specific steps required to verify and refine AI-generated content.

☐ Workflow expectations allow employees sufficient time to perform mandatory evaluations before acting on AI information.

Protection of Integrity

☐ We recognize that AI is not 100% accurate; therefore, human verification is a mandatory, integrated part of the workflow.

☐ We have a "No-Fault" reporting channel for AI quirks. We’ve made it easy for people to flag weird or wrong AI behavior so we can improve the tool as a team.

☐ There is a clear way for people to flag "Speed vs. Quality" conflicts. If the pace of the work is making it impossible to apply a professional "seal of approval," the priority is to adjust the timeline, not lower the standard.

Managerial Stewardship

☐ Managers are prepared to coach employees on how to use AI in ways that strengthen judgment and decision quality.

☐ Managers are prepared to coach their teams on when to override or question AI, protecting the time needed for human oversight.

☐ Managers support their teams in decoupling the pace of human analysis from the speed of AI generation.

Workload and Role Impact

☐ We have reviewed how AI changes job scope and responsibilities.
☐ We have adjusted workload to provide sufficient time for the front-loaded demands of AI integration, including learning, setup, data cleanup, and process redesign.
☐ Managers have and will continue to adjust workloads based on visible priorities.
☐ Expectations around pace and responsiveness are clear.

Identify the Non-Negotiables for your Culture

Before implementing new tools, Leadership must decide what remains non-negotiable.

What does human judgment mean to our organization?
What standards must never be compromised?
What does stewardship look like under pressure?

AI changes the rhythm of work.
Leadership determines whether that rhythm strengthens or destabilizes the culture you intend to build.

AI Is a Powerful Technology. Strategy Still Leads.

AI can generate volume, speed, and expansion, but it cannot determine what is worth pursuing. Strategic clarity must be the filter that determines what moves forward and what is set aside. Without it, you are simply accelerating in an unknown direction.

This is the first of a four-part series where I share the AI Implementation Checklist, developed through the ALIGN Method for Strategy, Culture, and Execution. We begin with the foundation: Strategy.

Last year I attended a LinkedIn-sponsored webinar on AI and leadership. One recommendation caught my attention: the presenter suggested that when a direct report comes into your office with a question, your first response should be, “Did you ask AI?”

As an organizational development practitioner, that direction raised several questions for me:

• Does AI have enough context to answer in a way that reflects the company’s values and strategic intent?

• If AI becomes the first stop for thinking, how do we ensure its answers reflect what matters most to the customer?

• What happens to the relationship between a manager and employee who value connection and mentorship?

• How does that shift redefine the function of the manager?

We often encourage employees to also present a solution when they present a problem. That is a healthy discipline. This felt different. It positioned AI as the first stop for thinking rather than a support to human judgment.

At the time, I was still getting familiar with AI. Still, a few warning signals went off. Since that webinar, I have used AI extensively. I find it incredibly helpful for clarifying my thinking. It often says succinctly what I have been struggling to articulate. It analyzes information quickly and suggests logical next steps without hesitation. It knows a lot about a lot.

I have also seen its limits:

• It will confidently make things up.

• It will exaggerate when it lacks context.

• It requires clear instructions to perform well.

• It moves quickly toward completion when nuance, judgment, and context still require human evaluation.

It is a powerful tool, but it requires thoughtful management. Every significant technology investment—ERP systems, CRM platforms, data dashboards—reflects the quality of strategy, the clarity of culture, and the discipline of execution. AI does as well. It simply operates at greater speed and with greater generative capacity.

The shift we are seeing:

• AI generates output.

• AI expands scope.

• AI increases volume.

• AI operates in ambiguity.

• AI fills in gaps when clarity is missing.

Whatever is strong in your organization becomes more visible. Whatever is unclear or misaligned also becomes more visible. Because the pace is faster, the consequences surface faster.

Many organizations are accelerating AI adoption because the pressure to keep pace is real. But an increase in volume does not require people to accelerate; it requires disciplined judgment. Strategy—and ultimately the benefit to your customer—becomes the filter that determines what moves forward and what is set aside. AI increases what is possible, but strategic clarity determines what is worth pursuing.

That is why alignment matters before implementation.

I developed an AI Implementation Checklist through the lens of an organizational development practitioner. It is designed to help leadership teams align strategy, culture, and execution so that AI strengthens the organization in deliberate ways. This first set of questions ask the important questions to ensure AI is in service to the strategic direction.

STRATEGY — Will AI help us advance what matters most?

Strategic Clarity

☐ We have identified the enterprise-level outcomes AI is expected to improve (e.g., growth, margin, customer retention, speed, quality).

☐ We have defined how customers will benefit, directly or indirectly.

☐ We can clearly explain why we are using AI.

Focus and Tradeoffs

☐ We have defined the initial operational problems AI will address.

☐ We have identified what tasks or projects will be paused to make room for AI integration.

☐ AI investments align with how we compete and grow.

Milestones and Horizon

☐ The original reasons for adopting AI have been translated into measurable milestones.

☐ Strategic objectives are mapped to 30–60–90-day milestones, followed by 6-month intervals through a 24-month horizon.

☐ Leadership will review progress at defined intervals aligned to these milestones and will make adjustments as needed.

In the next post, we will examine Culture: How will AI shape how we work together?

#WorkWiseStudio #AILeadership #StrategicClarity #OrganizationalDevelopment #LeadershipChecklist

AI: IS IT WORTH IT

Success with AI depends on how well the technology supports your people and advances your strategy.

In this five-part series, I am sharing how to use the ALIGN framework to help organizations integrate AI in ways that strengthen strategy, culture, and execution, and turn AI into a genuine strategic advantage.

In Absorb, leaders gather data to understand what is actually happening.
In Legitimize, leaders respond with a clear, prioritized roadmap that reflects what they heard from stakeholders, what the data reinforces, and what they observed firsthand.
In Integrate, leaders engage staff to translate the roadmap into practical, workable detail, aligning priorities, systems, and roles.
In Grow, leaders strengthen the organization’s capacity and confidence to carry the work forward.

Here, in Nurture, we focus on what allows the investment to pay off over time. Nurture is about sustained leadership attention, clear priorities, and ongoing stewardship that help AI mature into a reliable, effective part of how the organization operates.

Is It Worth It?

When leaders introduce new technology, the question underneath the launch is simple: is it worth it?

That question reflects the full cost of the investment. The cost of the tool itself. The cost to redesign workflows. The cost to integrate systems, train people, and support adoption over time. Leadership attention, organizational capacity, and opportunity cost all factor into the decision. The investment is financial, operational, human, and strategic, shaping how the organization competes and grows.

This series opened with research from McKinsey, The State of AI in 2025: Agents, Innovation, and Transformation. That report shows a consistent pattern. While most organizations are using AI in some form, only a small group report meaningful enterprise-level value. McKinsey refers to these organizations as AI high performers.

What distinguishes AI high performers is sustained commitment. They redesign workflows to maximize human and AI strengths across the flow of work. Senior leaders demonstrate visible ownership and remain engaged well after implementation. Measurement continues beyond early milestones. Training and support remain in place. Over time, usage deepens and value compounds.

This is how the original question, “Is it worth it?”, is answered. AI becomes worth the investment when commitment extends beyond launch and meaningfully shapes how the organization operates day to day.

In the ALIGN framework, Nurture is the phase where leadership commitment to the goals is critical to realizing the intended outcomes.

Nurture as a Leadership Practice

Nurture is a leadership responsibility. Leaders ensure the organization maintains focus on AI implementation and creates the conditions for it to mature into a highly effective tool.

That focus is supported through feedback loops. The success criteria that made the investment worth pursuing in the first place are translated into ongoing milestones with clear objectives. Progress is reviewed at meaningful intervals. Leaders remain curious about what the data, lived experience, and results are showing. Learning guides adjustment as conditions evolve.

From Champion to Steward

Once an AI tool goes live, leadership involvement evolves from championing implementation to stewarding long-term use.

Ownership remains clear. Resources stay aligned. Measurement reflects real operating conditions. Leaders stay connected to how the system supports daily work and decision-making. This continuity protects the original investment and sustains momentum.

RebalancE Work to Reach Equilibrium

AI changes how work is distributed across the organization. Some tasks move into the system. New responsibilities emerge around oversight, judgment, and coordination.

The role of leadership is to keep priorities visible and viable so the organization can make decisions consistent with those priorities. When leaders are clear about what matters now, what can wait, and what can be set aside, managers realign work accordingly.

Managers translate that clarity into operational decisions. They adjust workloads, sequence work, and integrate AI into planning and delivery in ways that reflect stable priorities rather than constant change. Tradeoffs become explicit. Some work is set aside in favor of efforts that add the most value. AI begins to relieve pressure in practical, observable ways.

Learn Through Ongoing Dialogue

AI capabilities continue to evolve. Nurture depends on staying in conversation with the people closest to the work.

Leaders establish regular opportunities to surface insights, constraints, and opportunities. Patterns appear early. Adjustments remain manageable. Trust grows as people see their experience reflected in how the system evolves.

Reinforce Purpose Over Time

As AI becomes part of everyday operations, an ongoing sense of purpose provides continuity.

Leaders reinforce purpose by recognizing effort as well as outcomes. Milestones reached, lessons learned, and improvements made are acknowledged. This attention signals that the work remains visible and valued.

Positive recognition sustains energy. Commitment strengthens as people experience support while working through discomfort and uncertainty. Purpose connects daily effort to the original intent of the investment.

The Payoff

Sustained commitment produces compounding returns. As capability deepens, confidence builds. As work becomes more coherent, capacity increases. As the organization becomes more effective in how it uses its time, makes its decisions, and gets things done, the payoff multiplies.

This is Nurture in action. The question “Is it worth it?” is answered when leadership remains engaged, stays focused, and adjusts based on what is learned about customers’ experiences, employees’ work, organizational dynamics, and system performance as the technology becomes embedded over time.

AI Raises the Bar

Success with AI depends on how well the technology supports your people and advances your strategy.

In this five-part series, I am sharing how to use the ALIGN framework to troubleshoot friction in AI implementations and turn AI into a genuine strategic advantage.

In Absorb, leaders gather data to understand what is actually happening.
In Legitimize, leaders respond with a clear, prioritized roadmap that reflects what they heard from stakeholders, what the data reinforces, and what they observed firsthand.
In Integrate, that roadmap meets the realities of daily work, where priorities, systems, and roles must begin to line up in practice.

In Grow, we explore ways to strengthen the organization’s capacity to carry the work forward.

Strength the Ecosystem

Congratulations. You have launched your AI initiative. Now the real work begins.

Once priorities have been translated into action during the Integrate phase, the next step is to strengthen the people and systems that will carry the work forward. This is the Grow phase, where leaders, teams, and individuals build the capacity, confidence, and resilience required to sustain progress.

A byproduct of AI’s ability to operate at a much faster pace than humans is that it accelerates decisions, exposes inconsistencies, and makes gaps in clarity, judgment, and leadership visible far more quickly than before. In doing so, AI introduces a new kind of pressure into the organization.

Grow is the phase where organizations pause long enough to understand their current state and identify where strategy, people, and processes must grow in skill and understanding for AI to be effective. Without this work, AI will amplify issues that humans might previously have corrected in the moment, issues that now risk being embedded into automated systems and scaled across the organization.

Reallocation, not Replacement

When people hear “AI” and “efficiency,” they often hear “replacement.” That fear is understandable. No one wants to feel that their judgment, experience, or contribution can be reduced to a machine.

The reality is that people and technology are good at different aspects of work. AI is well suited to speed, scale, and consistency. Humans are well suited to context, judgment, and meaning. Grow is about building the skills and knowledge that enable people to work at their best. In the context of AI implementation, Grow also focuses on maximizing human strengths so the technology is effective, making that division of labor explicit and workable.

While organizations may not explicitly state that they intend to replace people with AI, there is often a quiet hope that once AI is introduced, cost savings will be realized by reducing or stretching human involvement. What is often underestimated is the opposite reality: AI raises the demand for human capability. As systems move faster and decisions scale, organizations need clearer judgment, stronger decision-making, and more disciplined learning than before. When that capacity is not developed alongside the technology, AI exposes gaps that teams are not equipped to manage.

While this gap often shows up first in how leaders think, decide, and learn, it does not stay there. These demands quickly move into execution, shaping how work is paced, how risks are managed, how quality is maintained, and how people experience the culture under pressure. Grow is where strategic intent and cultural norms translate into how work actually gets done across roles and teams.

Strengths and Meaningful Work

As a Gallup Strengths coach, I am very aware that people thrive in different parts of execution. What feels energizing to one person may feel draining to another. Someone with Strategic may want to move quickly and adjust course as new information appears. Someone with Deliberative may want time to think risks through. A person high in Adaptability may shift naturally to meet the moment, while someone strong in Consistency finds meaning in stability and reliability.

What one person finds dull gives another person energy. What one person finds difficult is easy for another. There may be assumptions that certain kinds of work are inherently dull or undesirable while for many people they find deep satisfaction in work that is structured, repeatable, and predictable. They take pride in accuracy, continuity, and getting things right over time. That contribution matters. AI does not eliminate the need for those qualities. It changes where they are applied.

As systems take on more of the mechanical repetition, human work often shifts toward oversight, quality, exception handling, and judgment at the edges. For someone who values consistency or deliberation, this may mean becoming a steward of reliability rather than a processor of volume. For someone who values adaptability or strategy, it may mean focusing more on direction-setting and course correction. The work evolves, but the strengths still matter.

Grow is about helping people see how what they naturally do well continues to be valuable as the shape of the work changes. It is not about forcing everyone into the same kind of role. It is about redirecting strengths so people can contribute with confidence and pride as AI becomes part of how work gets done.

Personal Agency

Admitting where support is needed can be uncomfortable, especially in environments that reward competence and speed. Leaders can lower that barrier by starting with strengths. Naming what someone already does well, and why those strengths matter to the work or the team, establishes respect and context before discussing development needs.

From there, invite the individual to identify where additional support would be most helpful. When people are asked for their perspective first, the conversation shifts from evaluation to collaboration. The perceived risk drops, and participation in learning becomes more likely because it feels self-directed rather than imposed.

This process is more effective when leaders pair the conversation with a defined set of options. Offering a clear menu of development supports signals that help is real, available, and endorsed. People are more willing to name what they need when they know those needs can actually be met.

People at every level, from the front line to the C-suite, benefit from support that helps them calibrate their strengths in an AI-augmented environment.

Growth in Capacity Precedes Growth in Results

Many organizations name growth as a top priority while simultaneously contending with uneven execution, workforce strain, and unresolved questions about identity and direction. These tensions matter because AI does not operate in a vacuum. It operationalizes whatever clarity or confusion already exists in the system.

Organizations often articulate ambitions to use AI to improve efficiency, strengthen operations, or elevate the customer experience. Those outcomes are achievable, but only if the organization grows in parallel in several critical ways.

Grow focuses on building clarity and judgment so that speed does not outpace understanding.

A Critical AI Design Constraint

People routinely navigate ambiguity by applying context and judgment. AI does not have that context. When clarity is missing, it will still produce an output, but that output is based on statistical inference rather than situational understanding.

AI does not understand a situation. It recognizes patterns.

More specifically, statistical inference means that AI:

• Looks at large volumes of past data.

• Identifies patterns, correlations, and probabilities within that data.

• Uses those patterns to predict or generate what is most likely to come next, based on the inputs it receives.

What AI does not do:

• Understand why something matters in this moment.

• Grasp intent, consequences, or tradeoffs unless they have been explicitly defined.

• Sense shifts in tone, trust, pressure, or context the way people do.

• Adjust based on lived experience or values unless those are encoded into rules or training data.

When clarity is missing, AI does not pause or ask for meaning. It fills the gap by extending patterns it has seen before. This is why Grow matters.

Strategy (Including Brand)

Strategy sets direction. It establishes what the organization is trying to become and how success will be defined.

What AI can do

• Analyze large volumes of data to identify trends, opportunities, and risks.

• Model scenarios and tradeoffs based on defined objectives.

• Optimize toward stated goals and scale strategic decisions quickly.

What AI needs humans to be clear about

• What the organization is trying to become, not just what it is trying to improve.

• What differentiates the organization and what should not be optimized away.

• Which tradeoffs matter most when priorities conflict.

• How success is defined beyond speed, volume, or short-term gain.

Development focuses on strengthening direction-setting.

Examples of effective support include:

• Strategy clarification sessions that force explicit tradeoffs.

• Leader working sessions on framing useful questions and constraints for AI systems.

• Coaching senior leaders to articulate strategy and brand intent in operational terms.

• Scenario-based exercises that practice decisions with incomplete or competing data.

Culture

Culture shapes how decisions are made when pressure is high and priorities collide. It is experienced through what people believe will be supported when judgment is required.

What AI can do

• Apply policies, rules, and priorities consistently once expectations are clear.

• Reinforce patterns of work through scheduling, workflows, and automated interactions.

• Reduce variability in routine decisions.

What AI needs humans to be clear about

• How values are meant to guide real decisions.

• What matters when priorities compete.

• Where discretion is expected and where consistency is required.

• What people can trust will be supported when judgment is exercised.

Development focuses on shared understanding.

Examples of effective support include:

• Facilitated conversations using real decisions to explore how values apply in practice.

• Leader coaching on explaining tradeoffs, especially when decisions disappoint someone.

• Team forums that normalize naming tension instead of working around it.

• Clear escalation paths so individuals are not carrying cultural decisions alone.

Execution

Execution is how strategy becomes real in day-to-day work. It is the set of decisions, handoffs, and follow-through that determine whether priorities are delivered or quietly eroded over time.

What AI can do

• Monitor performance continuously and at scale.

• Surface patterns, anomalies, and early warning signals.

• Automate routine tasks and reporting.

What AI needs humans to be clear about

• Which signals matter and which can be ignored.

• What constitutes meaningful deviation versus normal variation.

• When human intervention is required and who is accountable.

• How decisions should be made when data is incomplete or contradictory.

Development focuses on judgment under speed.

Examples of effective support include:

• Helping leaders and managers interpret AI outputs in the context of real operating decisions.

• Practicing how to respond to early signals using live data, not hypothetical scenarios.

• Clarifying decision rights so accountability remains with people, not systems.

• Coaching leaders to intervene early and proportionately, rather than waiting for failure or overreacting to variation.

Normalize the Learning Curve

Innovation requires new skills, and proficiency takes time. Leaders play a critical role by modeling curiosity, calibrating expectations to the reality of learning, and creating conditions where learning is expected and supported.

Feedback as Fuel

Growth depends on feedback that is integrated into everyday work. When people see their insights shaping real decisions, trust increases and resistance decreases. Feedback becomes a source of refinement rather than a penalty.

The Result: A Culture of Continuous Learning

AI increases the demand for continuous learning. While there is a temptation to believe technology will reduce the need to build human capacity, this kind of technology does the opposite. It requires more clarity, more judgment, and more learning over time. When people do better, AI does better. In that way, AI becomes a reflection of an organization’s commitment to learning, especially when the pressure to move faster is highest.

UP NEXT: Nurture

In the next post, Nurture, we’ll explore the ongoing commitment leaders must make to protect, reinforce, and sustain the human practices that allow an AI-enhanced organization to realize its full potential.

Why Didn’t Anyone Ask Me?

Success with AI depends on how well the technology supports your people and advances your strategy.

In this five-part series, I am sharing how to use the ALIGN framework to troubleshoot friction in AI implementations and turn AI into a genuine strategic advantage.

• In Absorb, leaders gather data to understand what is actually happening.
  In Legitimize, leaders respond with a clear, prioritized roadmap that reflects what they heard from stakeholders, what the data reinforces, and what they observed firsthand.
  In this post, we focus on Integrate, the phase where that roadmap meets the realities of daily work.

When a “New Way of Working” Misses the Mark

Have you ever been told there was going to be a new way of working, and the moment you heard the details, you knew it was not going to work?

Maybe the plan sounded reasonable at a high level. But once you pictured it inside the flow of your actual tasks, it was clearly a non-starter. The natural response is often, Why didn’t anyone ask me?

When AI initiatives stall, it is usually because of this gap. The tool is being built or adjusted by people who do not have to live with the consequences of its output.

Organizations often limit participation to a small group in the name of efficiency, only to delay surfacing issues that later become harder and more expensive to fix.

The Integrate phase exists to close this gap.

Bringing the Doers and the Builders Together

Integrate brings the doers, both internal and external, and the builders to the same table.

In Absorb, the project team worked with leadership to synthesize input from staff, customers, and vendors. In Legitimize, that same team helped leadership assess what was feasible and set priorities.

In Integrate, we extend information equity to the people who actually carry the work forward.

Information Equity

Integration depends on transparency and shared understanding.

Sharing high-level themes from the Absorb Phase (discovery) helps staff understand the realities that informed leadership and project team decisions, while protecting the candor of those who contributed. This shared context reduces resistance and builds trust.

The Communication Loop

Information equity only works when communication flows consistently.

Because the project team helped shape priorities and sequencing, they are now responsible for keeping sponsors and impacted staff informed of progress. External partners do not need internal diagnostics, but they do need clear, targeted updates about changes that affect their work.

When everyone is working from the same source of understanding, attention shifts away from defending decisions and toward building the future.

Shared Design: From Mandate to Meaning

AI systems are often technically correct and operationally broken. The logic may be sound, but it frequently fails to reflect organizational values, institutional knowledge, and the nuanced judgment people apply every day to do the work well.

Shared design closes that gap. The project team works directly with the people who touch the work. If the AI is customer-facing, this may include trusted customers. If the issue is data quality, it includes the vendors supplying that data.

As teams move into the details, a second round of discovery typically occurs, one that focuses on practical realities and operational nuance. This deeper examination allows assumptions to be tested and adjusted in the context of real work.

When those who are impacted play an active role in shaping how the solution is designed and implemented, it is more likely to fit the realities of the work, reduce rework, increase adoption, and clarify risks and tradeoffs so the team can adjust course sooner rather than later.

Solve for the System, Not the Tool

During Integrate, the combined team wants to identify any friction across the entire ecosystem.

• Is the AI underperforming because vendor data is inconsistent?

• Does the output require multiple layers of verification by staff?

• Is a fix creating new hurdles for customers?

• Where have people created manual workarounds just to get their job done?

The tool is only one part of the system.

Work in Draft Mode

When a project is already strained, announcing a final fix increases risk. Instead, move into draft mode.

Choose one friction point identified by the people doing the work. Run a one to three week pilot with a small group of staff or a subset of customers.
Be explicit that this is a test. If it does not work, adjust and try the next draft.

Draft mode lowers the temperature and replaces pressure with learning.

Integration is where strong ideas become an operational reality

You do not need to involve everyone, but you must involve those who are materially impacted. When the people responsible for execution and the partners affected by the change have a voice in shaping the solution, implementation accelerates and resistance fades.

As noted in the first post of this series, many organizations are using AI tools without embedding them deeply enough into everyday workflows to realize sustained value. Integration is the work of closing that gap, so AI becomes part of the operating system, strengthening the system’s capability rather than standing apart as a separate solution or the answer in itself.

Up Next

Once AI is part of how work gets done, success depends on ensuring people are supported as roles, decisions, and expectations evolve. In the fourth stage of ALIGN, “Grow”, we reinforce skills, clarity, and confidence so individual and organizational capability continues to develop and move forward.

Yes, you have a point

Success with AI is not about the technology itself. It is about how the tool supports your people and advances your strategy.

In this 5-part series, I’m sharing how to use the ALIGN framework to troubleshoot friction in your AI implementation and turn AI into a genuine strategic advantage.

The Absorb phase was about gathering data to understand the current situation. The Legitimize phase is about respecting the people who shared their experiences and perspectives by responding with a clear, prioritized roadmap.

The Reality Check

Launching an AI initiative is an achievement. While we all want projects to go off without a hitch, sometimes we just don’t know things until we start. If outcomes aren’t lining up with expectations, consider it an opportunity to learn rather than a setback. Use this phase to identify gaps and recalibrate.

Gather the feedback you received during the Absorb phase and organize it into these three sources of friction:

• Strategy (The "Why"): Feedback regarding high-level goals.

  • Is the AI helping you move the needle on your core mission, or has it become a distraction?

• Execution (The "How" and "When"): Feedback regarding the daily reality.

  • Is the tool reliable, useful, and credible? Does it fit the workflow, or is it creating "shadow processes" and just too messy to be useful?

• Culture (The "Who"): Feedback on how the technology impacts your people.

  • Is it shifting how you live out your values or how you serve your customers and staff?

  • Do customers and/or staff feel undervalued, or ignored. Do staff staff feel like their jobs are threatened?

Make clear the Gaps

Use this simple audit for each major feature to highlight exactly where the project is falling short of the vision:

The Reality Gap:

What we planned: AI reduces administrative burden by 30%.

What we observed: Staff are spending 40% more time "babysitting" the AI's output.

The Verdict: The tool is functioning, but the data is unreliable.

Individually Review the data

Each leadership team member should review on their own the data collected during the Absorb phase. This includes insights from:

• Direct Conversations with project teams and users.

  • Note on Responsibility: Use discretion regarding names in the report. People can become fixated on "Who said that?" rather than "What is the problem?" If the culture has a tendency toward this, the person compiling the report should keep the findings focused on high-level themes.

• Feedback from impacted staff and customers.

• Data Trends and technical performance metrics.

• Direct Observations of the tool being used in daily workflows.

Reviewing this individually first allows leaders to process the "unfiltered truth" before the pressure of a group meeting begins. Some folks may feel "under fire," so it is best not to do this as a group initially. If the Project Sponsor is not on the senior leadership team, I recommend they be included in the review from the beginning. If that is not congruent with current practices, bring them in as soon as possible.

Lead with a desire to understand and empathy

The Empathy Filter: Appreciate the role and status of the person who shared the data. It may be anonymous, or it may be clearly identifed. Consider that each person is offering their “truth” their perspective informed by their experience. Their position, the level of that position, their time with the company, their comfort with AI, their comfort with change all are factors in their responses.

Take an Initial Pass: Mark each item:

• ✅ This sounds accurate to me.

• ❓ I need more information.

• ✖ I don't see this.

THe leadership gut check

“Change starts at the top” is a common refrain. I used to think that simply meant needing a strong sponsor to decree a project’s existence. Now, after years of organizational development and project management, I see it differently.

Leaders are often the primary obstacles to an initiative, sometimes unconsciously, and sometimes consciously as they protect their territory. The tragedy of leadership misalignment is that the staff are always the ones caught in the crossfire.

An effective leader must be brave enough to ask themselves hard questions before walking into the leadership team alignment meeting:

• Commitment: How committed am I, truly, to the success of this AI implementation?

• The Unspoken: What concerns have I been harboring that I haven’t shared?

• Vision: What does success actually look like from the perspective of my specific role?

• Self-Reflection: On the whole, am I helping or hindering this implementation?

Leadership Alignment Check: Four Essential Conversations

After the individual team members have had time to digest the information, the leadership team will begin a series of meetings with four distinct conversations to avoid "decision fatigue" and ensure raw data is fully understood before decisions are made or work is prioritized.

• Conversation 1: The Pulse (Review the Summary)

• Goal: Capture initial reactions without discussion. Look for "Small Wins", the parts that are working, to lead with when you eventually communicate to the organization.

• Conversation 2: The Context (Fill in Missing Details)

• Goal: Address items marked "Need more information." If the data doesn't exist, establish the metrics you need to track.

• Conversation 3: The Reality (Validate Assumptions)

• Goal: Compare initial project assumptions against the lived experience of the staff. What did we get right? Where were we blindsided?

• Conversation 4: The Alignment (Identify Priorities & Root Causes)

• Goal: Reach consensus on the "Why" we are doing this AI implementation and why we are having these issues. If leaders disagree on either the purpose or the root cause of problems, the resulting roadmap will be disjointed and the staff will get caught in the middle.

The Technical Reality Check: AI Recalibrations

Before prioritizing, apply a technical lens to determine if the friction is a human, data, or tool problem. This ensures your roadmap is grounded in reality:

• Instruction vs. Tool Failure: Is the AI failing, or is the "prompt" simply missing context? If it’s an instruction issue, the fix is better templates, not a new tool.

• The "Fabrication" Audit: Identify where the AI is generating confidently incorrect fabrications or "Logic Breaks." These are non-negotiable risks. Move them to "Stops" or "Mystery" immediately.

• Data Foundation Debt: Is the AI underperforming because internal data is messy? You may need to prioritize "cleaning the house" before the technology can deliver.

The Prioritization Filter

Now, filter the remaining feedback and technical requirements through the lens of Strategic Impact vs. Effort. At this stage, our goal is stabilization. We must address areas of frustration quickly so that people don't disengage from using the AI.

• The "Maintains": Start by identifying what is working well. These "Bright Spots" build confidence and provide a stable baseline for the team to lean on while other areas are fixed.

• The "Stops": Features causing enough friction to degrade the customer experience or data integrity. Once you've acknowledged the wins, you can objectively decide what to pause or pivot immediately to stop the "bleeding."

• The "Nuance Gaps": Manual workarounds necessary because the AI doesn't understand the job. These require training or process adjustments to eventually move them into the "Maintains" category.

• The "Mystery": Issues where you aren't sure of the root cause; give these more time with guardrails before deciding their permanent home.

The Responsive Roadmap

A roadmap in the ALIGN framework is a commitment.

• Immediate Fixes: Address the top 1–2 "Blockers" to show momentum and build trust.

• Strategic Adjustments: Realign the AI’s role to support the actual nuances of the work you identified in the Absorb phase.

• The Commitment: Explicitly state what you are not doing right now, so the team knows where to focus their energy.

It is really important to attach a high level timeline to the roadmap so that people know relief is on its way.

The Strategic Project Sponsor: Anchoring the Realignment

When the C-Suite recommits to the priorities, it is a good time to take a look at the project sponsor. It is common to appoint the CTO as the default Sponsor for AI just to get it off the ground, but as the project’s impact becomes clearer, you may realize the true owner should be the person who "owns" the specific strategic pillar the AI is meant to support.

The best Sponsor is the person who has the most to lose if the strategic goal isn't met. If the AI's goal is to reduce customer churn, the Head of Customer Success should likely be the Sponsor, with the CTO as a key Strategic Partner.

The Immediate Focus of the Strategic Sponsor:

• Before the roadmap is finalized, the Sponsor brings it to the project team for a "sanity check." By seeking their input on potential technical hurdles or "tweaks" before the final stamp of approval, the Sponsor demonstrates respect for the team’s expertise and ensures the plan is actually executable.

• They serve as the vital link between leadership’s vision and the project team’s reality. They ensure the C-Suite understands the technical "cost" of strategic pivots, while ensuring the project team understands the "why" behind shifting priorities.

• They ensure the "Stops" actually stop and the "Maintains" are protected.

• They protect the Project Manager and technical team from "scope creep" and competing departmental "asks" while the system is being stabilized.

Communicating the Road Map and Next steps

Legitimize is the practice of validating your team’s feedback, aligning leadership around immediate priorities and creating a prioritized roadmap to swiftly address concerns and limit frustration.

Staff will want to to know if they were really heard, and what is going to be done about it.

Deciding who communicates “Yeah - you have a point” is a strategic decision that depends on the level of disruption to customers and to staff. If this project resulted in High-Stakes Disruption to customers and/or to staff, breaking the trust of the customer, causing deep frustration, the CEO needs to be the one to step up. When the CEO validates the team's lived experience, it provides the psychological safety needed for everyone to re-engage.

If the issues were caught before things went entirely off the rails, then the project sponsor can likely communicate the priorities and road map with high level next steps to the staff. It is something you are going to want to thoughtfully consider to ensure a continuation of trust and buy-in.

The Goal: A Calibrated Ecosystem

If people must overextend themselves to meet a technology, the system is not correctly calibrated. In a well-calibrated ecosystem, technology supports the strategy and the people. When we align these elements, we fix a project and we build an organization capable of turning any disruption into a new way to thrive.

Next Post: Integrate. We will explore how the project team and impacted staff turn these priorities into actionable steps and daily practices.