Change management is better than what you’re doing.

My biggest pet peeve is when leaders use “change management” as a buzzword.

The meeting is ending, people are starting to gather up their things or open an email, and a leader mentions as an afterthought “…and we’ll definitely need change management on this one.” Everyone nods, continues to pack their bags, and heads out the door.

There are a few possible scenarios that follow.

• Everyone forgets the mention of change management until after go-live, when adoption is slow and people are getting frustrated. Then someone slaps together additional training or job aids.
• The leader assigns “change management” to a team member with no change management experience, leading to months of stress for this person, who does their best without having the skills or tools (and ultimately doesn’t make an impact, through no fault of their own).
• The team brings in a change management team or expert (internal or external to the company) but gives them weak direction, few resources, and little influence. They struggle to get what they need from stakeholders and never make any real difference.

Don’t call whatever that is change management.

The reason this bothers me is that change management is one of the few disciplines that gets mentioned and then immediately overlooked. You won’t hear a leader say the first part: “…and we need some operational support” without a second part: “…to make sure the process can integrate with our technology.”

As change managers, we are begging for the second half of the sentence. Why do you need change management?

• Are you worried about audiences embracing the change because it’s a dramatic departure from the norm?
• Is there a lot of new content for people to take in and you’re worried they won’t remember on the job?
• Are you worried about people knowing and hitting key deadlines?
• Are there teams across the organization who need to come together to make this change work?
• Are there stakeholder groups that don’t want this change?
• Does the effort have an extended timeline and need prolonged momentum?

Once you know the “why,” you can plan the “how” – the change management solution. For example,

• If you’re worried about people embracing the change, focus the solution on their motivation — connecting to their purpose, showing them the value they personally will see from the change.
• If you need change management because there’s so much new content, put the training solution into high gear. Pull out all the stops to make sure the content is visible, accessible, and digestible (especially once you go live).
• If people coming together makes you nervous, focus on cross-functional collaboration and creating spaces to bring ideas together.

The “how” gets you to the “what:” adoption and performance — people doing things not just differently, but differently in the way that is needed to realize value.

To use change management successfully, don’t leave it as an afterthought. Explore why you need change management and how you will do it, to get to the goals of your initiative.

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From Training to Performance.

Every year, government agencies invest heavily in training. They develop courses, fill their LMS platforms, and send employees through hours of instruction. Yet many leaders still ask: Why aren’t we seeing better performance results?

They’re seeing the gap between learning and doing.

In high-stakes, high-accountability environments like government, this gap isn’t just frustrating, it is lost opportunity to truly develop people potential and deliver on the promise of exceptional government services.

Agencies don’t just need people to know policies, systems, and processes; they need them to apply that knowledge accurately and consistently.

So, what’s getting in the way and how can we fix it?

The Challenges

Training in a Vacuum

Too often, government training is disconnected from daily work. Employees learn about systems or policies in theory, not in the context of real scenarios. That abstraction makes learning easy to forget and hard to apply.

Over-reliance on Information Transfer

We often assume that knowing leads to doing. But behavior science says otherwise. Knowing the steps to a process doesn’t guarantee following them correctly under pressure. Training that emphasizes knowledge over performance misses the point.

Lack of Reinforcement

Learning fades without follow-up. When there’s no coaching or accountability, people quickly revert to old habits, especially when those habits feel faster or safer.

Cultural and Systemic Barriers

Sometimes the problem isn’t training—it’s the environment. Employees may be trained to collaborate, but if performance systems reward individual output, they won’t change. When systems, leadership behaviors, and training are misaligned, progress stalls.

Bridging the Gap

Training and performance support must be designed with work performance in mind, from the start. Here are five ideas and two technologies to make that shift:

Meet people where they are.

The Five Moments of Need model by Bob Mosher and Dr. Conrad Gottfredson reframes learning as a continuous process. It identifies five key moments when people most need support: when learning something new, wanting to learn more, applying knowledge, solving problems, or adapting to change. The key is to align learning strategies to the moments of need. Formal training is important when learning something new, while on-demand performance support helps with application and change.

Example: A federal HR specialist uses formal training to learn a new hiring system (New), quick reference guides while processing applications (Apply), and updated resources when policy guidance changes (Change).

Build for behavior, not just knowledge.

Start with the end in mind: What do we want people to do differently? Define the critical behaviors, then design training that helps people practice and get feedback.

Example: Instead of lecturing on conflict-of-interest policy, simulate real scenarios where employees must make judgment calls and receive feedback in real time.

Align training with systems and culture.

If training teaches one thing but systems reward another, behavior change won’t stick. Before designing new learning, ask: What are we rewarding?

Example: Review performance metrics, SOPs, and feedback loops to ensure they reinforce the new behaviors, not the old ones.

Ground training in the real world.

Learning should feel familiar and actionable. Use real cases, language, and systems employees recognize.

Example: Partner with front-line managers to identify everyday challenges and build your training activities around them.

Reinforce with coaching and feedback.

Learning is a process, not an event. Incorporate follow-up discussions, manager coaching, and check-ins that show the behavior still matters.

Example: Create a “learning transfer plan” for supervisors to reinforce key behaviors during team meetings.

Make learning and performance support personal.

A Learning Experience Platform (LXP) delivers personalized, just-in-time learning tailored to each employee’s role, goals, and recent activity. It moves learning from compliance-driven to performance-focused. These systems are more affordable and capable than ever and provide a flexible, mobile resource tailored to the individual.

Example: A Contract Officers Representative (COR), updating a contract record might receive a recommendation for a short video on managing vendor performance — right when it’s most relevant.

Remove friction wherever you can.

A Digital Adoption Platform (DAP) provides step-by-step, on-screen guidance inside the applications employees use every day. This helps them perform tasks accurately without leaving their workflow.

Example: When a federal employee logs into a new acquisition system, a DAP can guide them through creating a requisition, explaining each field along the way. The result: faster adoption, fewer errors, and greater confidence.

The Opportunity Ahead

Government agencies face complex challenges, policy shifts, tight budgets, legacy systems, and evolving missions. But they also have a tremendous opportunity to lead with intention.

When agencies shift their focus from training delivery to performance enablement, they close the learning–doing gap. They create not just informed employees, but capable, confident professionals ready to deliver excellence where it matters most: on the job.

Want to explore the topic in more detail with John? Hop on his calendar: Book a meeting with John

Four Truths Leaders Can’t Ignore.

When two organizations come together – whether through merger, acquisition, or partnership – leaders often focus on systems, structure, and strategy. But beneath the org charts and integration plans lies the most critical and most overlooked factor: culture. It’s the invisible current that determines whether people row together or row in circles.

I spoke with Aarif Aziz, Chief Human Resource Officer at Culligan International. He has seen Culligan through many acquisitions in recent years, so he has a great perspective and valuable advice for companies navigating culture integrations.

Aarif and his team have plenty of lessons learned. “We’ve done 300+ acquisitions in the last 6–7 years. It was very easy for us to bring examples where things didn’t go well. And interestingly, all the examples which didn’t go well were centered around culture. The question I had was, with such a rapid speed of integration, did we really take enough time to bring cultures together? (I validated) with our leadership team…everyone felt yes, we could have done more.”

Aarif and his Culligan HR leadership team have learned a lot about integrating cultures. They know that culture integration doesn’t happen by accident. It requires intentionality, clarity, and a lot of leadership. These four truths can guide the way.

1. The right culture balances diversity and consistency.

Every organization brings its own legacy of behaviors, beliefs, and norms. When companies merge, the instinct is often to declare a “new” culture (or dig in on the “old” culture) and expect everyone to conform. But research and experience tell us that forced uniformity rarely works. It dismisses the strengths each legacy culture brings to the table and erodes trust.

Aarif agrees: “There are uniquenesses and strengths of these cultures. That’s why these companies were successful and it became a valuable opportunity to bring them under (our) umbrella.

What we don’t want to do to say: this is Culligan culture and then copy-paste across the companies. It won’t be a successful model. It will destroy the value of our people and their diversity of thought.

Having said that, there are a few (culture) threads which have to be common. So, if we can bring those common threads, (build) some common ground, and empower people to operate, I think we create tremendous value.”

The goal is intentional integration: honoring the best of both while building shared norms that support the new strategic direction. This isn’t compromise; it’s culture design. Leaders should ask:

• What aspects of each culture helped the organization thrive?
• What values and behaviors will fuel our future growth?
• Where do we need alignment to function as one enterprise?

The most successful culture integrations are guided by a clear north star: a unifying purpose or set of principles that give teams something to believe in together.

2. Culture integration starts with behavior change.

It’s tempting to define culture as a set of values posted on the wall. But values mean little if they don’t show up in the day-to-day actions of leaders, managers, and teams. Real culture change starts where real work happens — in behavior.

Here’s Aarif: “No leader who understands how business gets done will be dismissive of how behaviors impact outcomes. Culture is abstract, so it’s really important to start with behaviors, not with complex frameworks or models.”

Here’s how:

• Define the specific behaviors that represent the new culture.
• Equip leaders and teams with practical tools and language to enact those behaviors.
• Reinforce those behaviors through systems: recognition, performance management, communication.

Aarif adds this advice: “Focus on small behaviors which impact the culture and really center the conversations around it. Because when you focus on behaviors, you impact the change at the ground level. It is relatable. Use the right examples, use data, and create opportunities for reflection. People are smart enough to pick it up.”

3. Culture integration takes leadership at every level.

One of the biggest pitfalls in post-merger integrations is assuming culture is “owned” by HR or the executive team.

Aarif emphasizes the importance of leading culture change: “The face of the entire effort must be the CEO and the business leadership. If they are leading it, they will emulate the right behaviors. They will lay out the right expectations, and it changes from being a business initiative to a business imperative.

Almost every business has come to HR with a specific priority for moving the needle on culture by changing behaviors. Not as an ask from us, or a mandatory requirement. But as something they are suggesting and prioritizing. So, for me, that’s a big win, because it is not driven by HR. Our role is to be the catalyst. It is a business agenda, so it’s driven by the business leadership.”

Senior leaders are essential, of course. But culture integration happens in everyday interactions: team meetings, project decisions, customer conversations. That means everyone leads culture, whether they manage zero people or five thousand.

To support this:

• Give leaders at every level a clear role in the culture journey.
• Build their capability to coach, role model, and reinforce behaviors.
• Share stories and examples from across the organization that bring the culture to life.

Aarif adds that collaboration between leaders and employees is key. “I think our people are quite conscious that the company is responding and focusing on culture. So, our two-way channels… not (just) top down, but also…bottoms up…(are) helping immensely.”

4. Culture integration is not a project; it’s a process.

Perhaps the most dangerous myth is that culture integration can be “checked off” once the dust settles. In reality, culture work is never done. It’s a continuous process of alignment, reinforcement, assessment, and evolution.

Aarif knows how important the assessment part is. “If you have clear measurement, you are able to assess the progress toward integrated culture and business outcomes. Is it becoming better, not better? And why?

I think for me the measure of success is two things: how our people are feeling and our business results. We have ways to understand and see the pulse of our people, right? But the final measure of any of this is business success. Your goal: People are feeling great, and the strategy is clear. People know what they’re doing, and they’re focused on outcomes.

And continue to monitor and show progress and continued engagement. Otherwise, you end up losing after initial momentum.”

Especially in the months following a merger or acquisition, sustained attention is key:

• Use pulse surveys and feedback loops to measure how culture is taking hold.
• Revisit and refine your culture roadmap as the business evolves.
• Celebrate business outcome milestones but also acknowledge the messiness of change.

Think of culture like a garden. It requires planting, watering, pruning, and patience.

Culture can be your competitive edge.

Culture isn’t the soft stuff. It’s a hard differentiator. Companies that invest in deliberate culture integration post-merger are more likely to retain key talent, accelerate performance, and achieve strategic synergy.

Help your organization navigate these transitions with empathy, structure, and behavioral science.

Want to explore the topic in more detail? We’d love to chat: Book a meeting

How Professionals Stay Smart in the Artificial Intelligence Age.

A user once asked a generative AI tool to come up with an original idea for children using a Lego set. The tool’s answer: “Imagine a Lego set that allows you to build a fully functioning time machine with intricate details and moving parts. This set combines the fun of building with Legos with an educational twist, teaching kids about historical eras and famous landmarks as they embark on time-traveling adventures.” What? Imagine the health hazards, the lawsuits, the damage to our current timeline…

Ok, that’s a delightfully harmless example. (Well, until we invent time travel anyway.) But misinformation isn’t always so obvious.

And we need to know when AI gets things wrong, because the consequences can range from funny to embarrassing to catastrophic.

Inaccurate data, flawed guidance, or hallucinated case studies can erode trust, trigger poor decisions, and damage your relationship with your team or your customers.

Nowadays, we pretty much have to use artificial intelligence, right? From generating marketing content to summarizing research and writing code, AI is saving time and unlocking creativity. It feels like if you’re not using it, you’re a step behind.

The good news: you can harness AI’s power without falling victim to its little robot lies.

The Misinformation Problem

The term “hallucination” is often used to describe when generative AI tools produce information that sounds plausible but is oh so wrong. These tools are powerful language models, not search engines. They don’t take a skeptical view or verify sources. They predict language based on patterns, not validity.

In 2023, a New York attorney used ChatGPT to draft a legal filing that cited six entirely fabricated cases. The AI-generated cases didn’t exist, but they looked real enough to pass an initial glance. The result? Sanctions and professional embarrassment. (Source: NYT)

Think about the high-stakes situations you might confront:

• A strategy deck citing false data could mislead executives and derail decisions.
• An AI-written employee communication could spread confusion if it includes misquotes or outdated policy references.
• A government contract could be rejected if AI invents credentials or claims.

Misinformation doesn’t always look like fiction. It often seems credible.

Three Traps for Business Professionals

Overtrusting Output

AI sounds confident. Its tone is polished. But confidence is not accuracy. (We all know people who fit this profile, right?) Professionals pressed for time might generate, copy, paste, and trust without verifying.

A psychological dynamic called “authority bias” is to blame: we tend to trust information from sources that “sound” authoritative, even if they aren’t.

False Citations or “Source Laundering”

Some generative AI tools fabricate sources or mix real citations with fake ones. Even when sources are accurate, they may be out of context or misrepresented.

In one test, ChatGPT cited a Harvard Business Review article that didn’t exist, but with a title and author combination that seemed plausible.

The Chicago Sun-Times published a 2025 Summer Reading List recommending 15 titles. The problem: ten of them were not real. The journalist relied on a third-party source that had used AI to generate the list.

A separate news item found that if you ask Chat GPT for links to sources, and there aren’t any, it will simply make them up.

Context Collapse

AI lacks situational awareness. It may pull ideas from unrelated fields or fail to consider the unique regulatory, cultural, or industry context that matters in your decision-making.

Five Ways to Stay Smart and Safe with AI

Always verify sources.

If AI offers a citation, check it manually. Follow the link. Search for the document. If it doesn’t exist, that’s your first red flag.

Pro Tip: Use AI tools like Perplexity.ai or Consensus.app, which prioritize sourcing and transparency over polish.

Add a layer of human judgment.

AI can accelerate your thinking, but it should not replace it. Ask yourself:

• Does this make sense in our context?
• What’s missing?
• Who would be harmed if this were wrong?

Think of AI as your intern, not your expert advisor. Its job is to help you think, not to do your thinking for you.

Use AI transparency settings.

Tools like ChatGPT Enterprise or Copilot often offer audit trails or cite where their information came from. Use these features to assess credibility.

If you’re using AI inside your organization, push vendors to explain how their models generate outputs and what guardrails are in place.

Insist on a human in the loop.

In regulated or high-stakes industries (e.g., healthcare, finance, government), build processes that require human review before AI-generated content is published or decisions are made.

This aligns with the GROW coaching model: AI may help define the Goal and assess Reality, but Options and Will must come from human insight and accountability.

Train teams to spot and stop AI misinformation.

Embed AI literacy into onboarding, upskilling, and leadership development. Teach employees:

• How to question AI output
• What to verify (and how)
• When to escalate concerns

And remember what we change management pros preach: changing behavior requires awareness, engagement, action, and reinforcement.

The Enemy

It’s not generative AI. Complacency is the enemy.

Generative AI isn’t malicious. It’s simply not designed to be truthful. It’s designed to be useful. As business professionals, it’s on us to pair AI’s speed and creativity with our discernment and ethics.

The most dangerous misinformation isn’t always the most outrageous. It’s the quiet, almost-right statement that slips through our filters because we’re too rushed, too trusting, or too dazzled by the tech.

In the age of AI, wisdom isn’t knowing everything. It’s knowing what to double-check.

A Simple Accelerator for Change Communications.

People resist change. You’ve heard it, read about it, and experienced it first-hand.

But you have a big change initiative upcoming in your organization. Maybe it’s a new technology, an acquisition, a new process… You’ve already heard people don’t want it. They want things to stay the same.

So, you’d better start turning that resistance around, right? Winning the hearts and minds of everyone you need to adopt this change.

Not so fast. You don’t need to combat resistance on every front. You don’t need to reach everyone, just your sweet spot.

Don’t waste time on those dead set against this change. They’ll never come around, and you don’t need them to.

Don’t waste time on those who are already on board. You will be, as they say, preaching to the choir.

Spend time on those in the middle – mildly supportive to mildly resistant – and who matter when it comes to the success of your project.

That’s your sweet spot. Get them, and you’ll win.

1. Identify your stakeholders. Group them in whatever way makes sense for your project: by business unit, function, role, and/or geography.
2. Map them. To do this, figure out two things: their level of resistance or support of the change, and their level of influence on the success of the change.

Here’s an example grid you can use to map your stakeholders.

As you can see, the sweet spot includes those who can influence your success, and those who are not firmly for or against. Focus your energy there.

3. Engage the sweet spot. To start, you need to understand each group in your sweet spot.

• What do they care about? How does this change address those things?
• What are the benefits and opportunities for this group?
• What challenges will the change pose for them?
• What are the consequences of non-compliance?
• What channels do they prefer for engagement and communication?
• What kinds of words or images appeal to them?
• Who are the people who influence them?
• What is their history with similar changes?

Answering those questions will help you craft an “experience plan” for each group, to begin moving them from awareness to engagement to adoption to ownership.

So, do you ignore the hecklers? No. Give them all the support you are giving employees in their stakeholder group, like communication, training, and post-launch support. Just don’t spend extra energy trying to turn them around.

This is different from what I was originally told years ago. “Find the naysayers and turn them around. Naysayers will tell you where your blind spots are. They will ultimately be your biggest advocate.” The research says otherwise. Most of the naysayers won’t get on board.

As you engage the sweet spot and the momentum shifts toward your change, the highly resistant will quiet down or change their minds.

Consensus is not the goal. Adoption, ownership, and performance are the goals. Every person in your organization doesn’t have to agree with every decision made. But if it’s a sound decision, you need to make its implementation a success.

How to Get What You Want When You Don’t Know What You Want.

It’s the kickoff meeting with the change management consultant for your project. In an ideal world, you know what goals you want to hit, and you understand the consultant’s approach to getting you there. But what if neither is true?

Confusion. Awkwardness. Wasted time. Opportunity?

Yes, that last one. Because if you have a good consultant, this is the beginning of a beautiful partnership.

Why? Because think about the flipside – you both think you know exactly how to proceed. That’s a recipe for disappointment.

Too often, consultants and clients think they’re aligned.

They charge forth without setting a foundation for clarity and trust. Then they have to course-correct, sometimes with painful consequences.

Not knowing is a gift – it forces you to discover, align, and work together.

So, how should your consultant set this foundation?

Discover.

Your change consultant should get themself up to speed and ask for your help to do it. Instead of making you explain and show them everything, they should respect your time and do some homework. Here are some of the things they can do:

• Review organization documentation. The consultant should review the mission, vision, and values of your organization. They should also familiarize themselves with the org chart, key roles, and the geographic layout of the organization.

I once worked with a team that had a value around “community impact,” and it kept showing up in small decisions. Knowing that from the outset helped me frame every change in terms of how it affected their mission, not just their margins.

• Review project documentation. The consultant should study the business case, plans, project team org chart and roles, tools to be implemented, and any deliverables created to date. They should also review your organization’s approach to change management, if you have one.
• Observe. Is there a facility or plant tour that would give the consultant a sense of the work of the company and the work environment of stakeholders? Could they shadow key roles to capture a “day in the life” of employees? Can they sit in on meetings? They should ask you to set those observations up for them.
• Conduct interviews. The consultant should talk to key people about the change facing your organization. This will give them the mindset of key players and your company’s environment and culture. They should ask open-ended questions like, “How would you describe the change ahead?” “How do you and others feel about it?” “What are the biggest risks?” “What do you hope for once this change is implemented?”

I remember asking a stakeholder, “What does this change mean to you?” and she replied, “Honestly? I’m just scared it means more work with less clarity.” That moment shaped how we approached the communication plan—we made transparency one of our north stars.

Answer the big three.

What does success look like?

Your consultant needs a crystal clear view of what success looks like for this initiative. And so do you! Getting to a shared understanding of the goals of the change is essential, before you start. That’s what you’re both working toward.

• Quantitative Goals. Hopefully you have something to share with your consultant – a business case for the project, strategic goals for the near-term, KPIs this change will help you hit… This will give your consultant clear targets, so they can make sure the change management approach points toward the center.
• Qualitative and Broader Goals. Near-term quantitative goals always have a “so what?” attached. For example:
  • Quantitative Goals: Adoption of the new system on Day One will save a certain amount of money (avoiding lost performance after go-live) and make a certain amount of money (selling a new product, etc.)
  • Broader Goals: This will expand the customer base and allow the company to grow.
  • Qualitative Goals: The new system and employees performing well on Day one will improve customer satisfaction, boost employee morale, and allow employees to develop faster through higher-level work.
• Personal Goals. You might have hopes and dreams attached to this change project, and that’s important information for your consultant.

Maybe opening a new facility is something you’ve imagined for years. Maybe you want to see the looks on your team’s faces when they love their jobs just a little bit more. Maybe this new project will help you hit your next career milestone.

Your consultant should be working to get your organization and you what you hope for.

I once worked on a project with a major retailer, and the client confided that if this system rollout went well, it would give her the credibility to throw her hat in the ring for a VP role she’d been eyeing. Knowing that gave us both extra motivation to make sure the project told a story of her leadership.

How will we get there?

• Your consultant should have a change management approach to get you to that success. They should walk you through it, step by step.

But if your organization has a change management model/approach/function you want your consultant to use, they should be able to do that and, importantly, describe to you how they will align with each step. Make sure your consultant has experience using their clients’ models.

• They might have a change diagnostic. This will show you your organization’s readiness for the change ahead in a number of key areas. This will do three things:
  • Identify where you need to focus. The diagnostic will identify gaps in your readiness, so you can channel your energy there.
  • Align key people on the landscape – the assets and liabilities – that you’re starting with.
  • Provide a dashboard to use throughout the project. You should come back to the dashboard periodically, to make sure you’re closing those gaps in time for your launch.

The diagnostic I use with Emerson clients rates readiness of 17 elements that map to our change model. We do the diagnostic in a working session with key clients, to surface all information, align on the current state, and agree to use the dashboard throughout the project.

One client described the diagnostic session as “like holding up a 360-degree mirror to the organization. Some of what we saw wasn’t pretty, but it was real, and we needed it.” That honesty helped set the tone for an open, focused partnership.

• Talk with your consultant about a culture assessment. It’s essential to understand what works (and what doesn’t) in your organization.

The consultant might do a “quick and dirty” culture assessment through interviews or conduct a more formal assessment. Then they should tailor the approach to the culture. Bottom line: if you want the change management approach to work and your change to stick, you need to go with the culture, not against it.

How will we work together?

Your consultant should want to know how to work with you best. Beware of consultants who simply inform you how they plan to communicate and collaborate. And don’t insist on a working approach that fits only you. This should be a conversation, ending in a working agreement that serves both of your styles and needs.

At a minimum, talk about:

• What checkpoints and decisions you need.
• Who needs to be involved in each decision or deliverable. Consider a RACI chart for the key people in your organization, so the consultant understands exactly whom to loop in, and how.
• How you like to communicate, and how often. What platforms do you like: email, messaging, texting, face-to-face, phone calls, shared documents? How often od you want to talk or collaborate? How much information do you want? What situations should trigger immediate communication?

Pro tip: Create a one-page working agreement. I once had a client who preferred Microsoft Teams messages over emails and wanted short audio recordings instead of reports so they could get caught up during their commute. That little note saved us countless misunderstandings.

• How you’ll handle roadblocks or resistance. What should your consultant do if they get push-back, inefficiency, or silence?

Your consultant should document your working agreements – nothing fancy, just a one-page outline of what you’ve agreed to. It might seem unnecessary, but it will prevent confusion when the project heats up.

Formalize it.

For each question, type it up and say it out loud – together. There’s no skipping this step. Have the consultant restate your wishes and agreements to make sure you’re on the same page. Think about it – what did you miss? When you’re both satisfied, share the documented approach, goals, and working agreement.

I once worked with a nonprofit that had just gone through a leadership change. We created a framing document outlining what success looked like and how we’d get there. A few months in, I noticed they were subtly shifting direction. I brought the document to a check-in, and sure enough—the new leadership had moved the goalposts. We updated the plan together, and from then on, reviewed it monthly. That simple document became our lighthouse.

Work the plan.

The plan – everything you’ve documented – is a living thing. Your consultant should revisit those key documents regularly (especially in the first few weeks) to document progress and make sure those plans still serve you based on emerging information. If not, revise them and make a new agreement.

When things get messy (as they often do) this work you did up-front will become your anchor and your way through the fog.

You didn’t engage a change management consultant to type up documentation. And you certainly didn’t hire them to tell you and your organization what you need. Neither of you has all the answers. It’s a partnership – you bring the organizational and industry expertise, and they bring the change management experience, informed by decades of big changes across many organizations. The synergy is what will get you to your goals, once you figure out what they are.

A Public Sector Leadership Imperative.

I recently read a departmental memo that struck all the right chords, clear, empathetic, visionary. But something felt off. It was too polished.

As it turns out, the memo was AI-generated. It made me pause and reflect: in a world where communication can be simulated at scale, what does it mean to be authentic?

For public sector leaders, this question isn’t philosophical, it’s practical.

The New Authenticity Gap

Artificial intelligence is changing the landscape of leadership. From policy briefs to constituent outreach, AI tools can now mimic tone, sentiment, and insight with remarkable fluency. But imitation isn’t connection.

In public service, trust isn’t earned through perfect prose, it’s earned through presence. Through consistency. Through leadership that feels grounded in real values and experience.

The risk is this: as the tools get better, the human voice becomes harder to distinguish and easier to question.

Public servants and employees are already predisposed to skepticism. Negativity bias tells us that people tend to focus more on what feels false or manipulative. Add in confirmation bias, and you’ve got a workforce that may interpret overly polished AI-generated messages as just more evidence of top-down detachment.

What Does It Mean to Be Authentic?

Let’s get practical. Authenticity isn’t about oversharing or rejecting innovation. It’s about alignment between what we believe, what we say, and what we do.

In change leadership, it’s called the “Say-Do Gap” — the space between what leaders say they value and what their actions demonstrate. Authenticity is about narrowing that gap.

Why is this so important now?

• In times of transformation, when budgets are shifting, roles are evolving, and systems are being reimagined, this alignment is the foundation for real trust.
• In high-stakes, high-scrutiny environments like the public sector, this alignment is everything. Employees and constituents are watching closely. “Do you mean what you say? Will you follow through?”

When there’s a mismatch — when messages feel manufactured or disconnected from reality — the trust erosion is fast and hard to reverse. But when words and behaviors align over time, even imperfect communication carries weight.

How Public Sector Leaders Can Stay (and Feel) Authentic

Here are five practical ways to embrace both technology and human nature to effectively lead in the evolving age of AI:

1.    Be transparent.

You don’t have to disclose every tool used, but when appropriate, naming the role AI plays in your communication can build trust, not erode it. People appreciate honesty over polish.

2.    Don’t outsource your voice.

Generative AI can be a powerful first draft partner. Use it to save time, explore tone, or structure messages. But let your lived experience and leadership point of view shape the final product. If it doesn’t sound like you, it won’t feel like leadership.

3.    Practice strategic self-disclosure.

Public servants aren’t looking for confessions; they’re looking for context. When you share a personal experience that aligns with a policy, priority, or pain point, it signals empathy and being grounded.

4.    Lead with consistency, not performance.

Authenticity isn’t a one-off act, it’s cumulative. As your words and actions align over time, you will build goodwill and trust. This “conversational capital” becomes especially valuable during times of high-stakes change.

5.    Prioritize presence over perfection.

Flawless communication isn’t the goal. Feeling seen and heard is. Sometimes the most effective thing you can do is show up, listen actively, and speak from the moment even if it’s not fully scripted.

The Human Advantage

AI can replicate tone. It can scale messaging. But it can’t lead.

It doesn’t carry the weight of responsibility, the courage to be vulnerable, or the insight that comes from years of public service. Those are the things that make leadership human. And in this rapidly evolving age of AI, they’ll be the things that make leadership matter.

By the way: I used AI tools to support the drafting of this post, but all ideas, insights, and final edits are my own.

Want to explore the topic in more detail with John? Hop on his calendar: Book a meeting with John

And How to Do AI Better.

Artificial Intelligence has the potential to transform how organizations work, innovate, and serve customers. Yet many leaders find themselves underwhelmed by the results of their AI initiatives.

In fact, new data from MIT show that 95% of AI pilots are delivering zero measurable return!

Why? Because the problem usually isn’t the technology. It’s how you’re using it.

Here are the five biggest mistakes:

1. Your data isn’t ready.

The old adage applies: garbage in, garbage out. If your data is messy, inconsistent, or incomplete, AI can only amplify those flaws.

• Is your data structured in a usable way?
• Are you using a data lake or other scalable storage strategy?
• Did you flood your LLM with everything you had, without cleaning, tagging, or segmenting it by relevance?

Raw data without curation leads to weak insights. AI’s output is only as strong as the input it’s given.

2. You implemented without a strategy.

Too often, companies pursue AI simply because everyone else is doing it. That approach almost guarantees disappointment. Successful AI adoption requires:

• A strategy aligned with business outcomes.
• Clear metrics for value (beyond “hours saved”). Think faster time to market, improved customer experience, or stronger employee engagement.
• A focus on use cases, not hype. AI should solve real business problems, not be a vanity project.

If you deployed AI without knowing the problem you wanted it to solve, you’re wasting your investment.

3. You didn’t prepare your people.

AI changes how people work. It requires different ways of thinking, new workflows, and new communication patterns. If your workforce hasn’t been:

• Trained in how to interact with AI,
• Guided on how their roles will evolve, and
• Supported in building new skills

…then you’re in for employee resistance and underperformance.

4. Your prompts (and people’s AI literacy) are weak.

Large language models don’t just “know” what you want. They need to be guided. That’s where prompt engineering comes in. It’s an art as much as a science. Weak, vague, or overly broad prompts generate disappointing results. Strong prompts, by contrast, can unlock nuanced, actionable insights.

But prompts don’t live in a vacuum. Without AI literacy, your workforce won’t understand how AI works, its limits, or its ethical considerations. Teaching people how to think critically, ask better questions, and apply responsible practices is the foundation of writing better prompts.

5. You underestimated change management.

AI adoption isn’t just about technology; it’s a change initiative. Like any organizational change, it requires leadership sponsorship, communication, and reinforcement.

And here’s the critical piece: storytelling. You must tell AI success stories in a way that makes employees feel part of the journey.

Numbers and technical jargon don’t inspire people to change behavior — stories do.

When leaders frame AI as a story of empowerment, growth, and human/AI collaboration, adoption accelerates and resistance fades.

Done well, storytelling removes fear. It helps employees see themselves as an essential part of the organization’s future.

AI success doesn’t come from buying the latest tool or chasing the latest trend. It comes from laying the right foundation:

1.  Clean, structured data.

2.  A clear strategy with measurable outcomes.

3.  People who are prepared, skilled, and literate in AI.

4.  Strong prompts fueled by critical thinking.

5.  Change management fueled by storytelling.

Organizations that master these fundamentals are the ones realizing AI’s full potential – and the ones who won’t be left behind.

References:

Chari, P., Challapally, A., Pease, C., Raskar, R., & Nanda, M. (2025). State of AI in business 2025. Project NANDA / MIT.

Perry, J. M. (2024). The AI evolution: How leaders can build an AI-native organization. Vibes AI Press.

You can win if you avoid these pitfalls.

We’re all witnessing the transformative potential of Artificial Intelligence (AI). From streamlining operations to unlocking new customer insights, the promise is immense. But as many business and IT leaders are discovering, turning those AI dreams into reality can be a bumpy ride.

How often do AI projects actually succeed? According to research by Harvard Business School’s Iavor Bojinov, the current success rate of AI projects hovers around a sobering 12%.

The current ROI on most AI initiatives is overwhelmingly low.

Leaders are compelled to invest based on AI’s ethereal promise, but in the short term, the current financial returns are just not there.

So, how can we buck this trend and ensure AI initiatives deliver tangible results? Bojinov’s insightful work, including his HBR article Keep Your AI Projects on Track, provides crucial guidance for leaders.

The Pitfalls and How to Avoid Them

Bojinov’s research highlights several common challenges that derail AI projects.

• Lack of Clear Business Objectives: Many initiatives kick off with the “cool” factor of AI rather than a specific problem to solve or opportunity to seize.

To overcome this temptation, start with a clear business need. Don’t let the technology lead; let the business strategy drive your AI efforts.

Ask, What business outcomes are we trying to achieve? How will AI help us get there?

• Data Dependencies and Quality Issues: AI thrives on data, but often the data is siloed, messy, or insufficient.

Leaders must understand the data landscape early on. Invest in data infrastructure and governance, as a big chunk of an AI project timeline is often devoted to data preparation.

Ask, Do we have the right data, in the right format, and of sufficient quality to train and deploy our AI models effectively?

• Talent Gaps and Integration Challenges: Integrating these solutions into existing systems and workflows can be a major hurdle.

Building and deploying AI solutions requires specialized skills. Take a multidisciplinary team approach that bridges the gap between business understanding, data science expertise, and IT capabilities.

Ask, Do we have the right talent in place, or a clear plan to get it? How will our AI solutions integrate with our current technology stack and business processes?

• Traditional IT Development Approaches: Long projects with a broad scope put AI projects at risk because they lock you into a solution from the start.

AI projects are often exploratory by nature. First, AI innovation is moving fast, so you’ll want to take the latest thinking into account. Second, you need to test and confirm what works for your company. Using an iterative or Agile approach, you can bring in new ideas midstream and “fail fast” to land on the best outcomes.

Ask, How can we create a nimble project? What mindsets and processes do we need to innovate, test new solutions, and incorporate lessons learned?

• Overlooking the “Human” Element: Resistance to change, lack of trust in AI-driven insights, and inadequate training can all hinder adoption.

AI implementation isn’t just about technology; it’s about people. Bojinov underscores the need for change management and clear communication. For example, engage stakeholders early and often. Focus on how AI can augment human capabilities rather than replace them.

Ask, How will we prepare our employees for these changes? How will we build trust and ensure the adoption of AI-powered tools and insights?

The Takeaways for Leaders

Bojinov’s work provides actionable insights for successful AI initiatives:

• Focus on business value first. Define specific, measurable business goals before diving into technology selection.
• Prioritize data readiness. Invest in your data infrastructure and ensure data quality is a top priority.
• Build collaborative, cross-functional teams. Foster communication and collaboration between business, IT, and data science teams.
• Embrace iteration and agility. Adopt an agile approach that allows for learning and adjustments along the way. Break down large projects into smaller, manageable milestones.
• Don’t forget the people. Plan for change management, communication, and training to ensure successful adoption.

The potential of AI is undeniable, but realizing that potential requires a strategic, business-driven approach. By learning from the challenges and adopting these principles we can improve the success rate of our AI initiatives and unlock the true value of this transformative technology.

And they have nothing to do with technology.

In the age of generative AI, agents, and other AI accelerators, the biggest threat to teams isn’t obsolescence, it’s underestimating the human factor. You have to think about tools and talent — both must evolve together.

As AI adoption accelerates, three elements of “talent” are more critical than ever: durable skills, emotional intelligence, and change management.

Durable Skills: The New “Hard Skills”

Durable skills are the utility players — things like critical thinking, communication, adaptability, problem-solving, and collaboration. They’re essential and independent of the tool or the context. They don’t expire with your next software update.

Why do you need durable skills now?

AI handles discrete tasks well. Context, nuance, or ambiguity? Not so much.

AI has the potential to flood the organization with output. Durable skills help teams make sense of it.

For example, AI can summarize the decisions made in a meeting, but only a person can interpret the implications of those decisions across real, specific stakeholder groups. Only a person can translate decisions into culturally consistent communications that land and resonate. Only a person can anticipate which stakeholders might resist or be early adopters of the changes to come.

Teams that lack durable skills may misuse AI, underuse AI, or misinterpret its outputs.

Emotional Intelligence: The Human Edge in the Age of Machines

Emotional Intelligence (EI) is the ability to recognize, understand, and manage the emotions of yourself and others. In an organizational context, we use emotional intelligence to influence, persuade, motivate, and manage others.

Why do you need emotional intelligence now?

AI without EI is doomed to failure. AI is a big change; moreover, it feels like a big change to people, because it’s such a hot topic. Are people afraid of being replaced or overwhelmed? News that AI is entering the workplace can trigger fear, confusion, and disengagement.

That’s why you need high-EI leaders during your AI rollout. They have the ability to detect unspoken cues (tone, silence, nervous behaviors), acknowledge them in a constructive way, convey information with sensitivity, and ultimately turn negative reactions into excitement and momentum.

But beyond the launch, you need AI to be a tool and a partner. One of the reasons for AI is to elevate your teams’ performance, right? Then you need synergy between employees and their AI agents. That’s where EI comes in. Emotionally intelligent teams promote curiosity and create the psychological safety necessary for risk-taking and innovation.

Change Management: The Accelerator (or Brake) on AI Success

Change Management includes:

• Leaders aligned on a clear vision and a compelling message for the change.
• Stakeholder engagement from the start.
• A detailed understanding of the impacts on each stakeholder group.
• Ways to engage the workforce and bring them from resistance to momentum to adoption to performance.
• Training that includes both the “why” and the “how.”
• Ways to sustain engagement and performance after launch.

Why do you need change management now?

Resistance to new technology is normal. Resistance to AI is certain. Ignoring it is fatal.

AI is a technology change, a process change, a mindset shift, and a performance challenge all in one. It’s a new way of working. It needs change management.

And, because AI is uncharted territory for most organizations, AI change management has to be current, nimble, and handled by your sharpest change agents.

AI doesn’t eliminate the need for people; it raises the bar for what people need to do well. No wonder some find it scary. Winning organizations are the ones that deeply value people and the unique skills they bring to the AI-enabled organization.

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