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.

Want to explore the topic in more detail? We’d love to chat: Grab a virtual coffee together

Four Ways AI Can Help Change Management Practitioners.

When you are leading a major transformation — an ERP implementation, an operating model redesign, a merger — one thing becomes clear, fast: even the best project plan does not guarantee people will adopt the change.

That is where change management comes in. And today, change professionals have a new tool in our toolkit: AI.

Used well, AI can accelerate outcomes, improve precision, and reduce risk. Here’s what it can help us do:

1. Surface what matters, faster.

Large-scale change generates a huge volume of data, like stakeholder feedback, pulse surveys, support tickets, and internal chat. AI can analyze that data in real time, identify sentiment trends, and flag emerging resistance. Instead of waiting for issues to escalate, we can respond early — with targeted interventions that matter.

2. Personalize the experience at scale.

Diverse groups need different messages, different training, and different levels of support. AI allows us to segment audiences intelligently and tailor communications and learning experiences without increasing headcount. The result? Higher engagement, faster uptake, and less noise.

3. Forecast risk with data, not just instinct.

We have all relied on experience to anticipate resistance. Now, we can combine that instinct with AI-driven models that flag risk area, based on real behavioral patterns and prior project data. This lets us get proactive, not just reactive.

4. Free up humans to do what humans do best.

AI can manage repetitive work: drafting initial communications, organizing feedback, or summarizing survey results. That frees up change leaders to do the higher-order work: building relationships, managing stakeholders, and navigating the culture. In short, it lets your team stay focused on the “human” side of change.

Here’s how I’m putting it into practice.

I have started to apply AI in small, practical ways to support my clients:

• I launched a brief survey to gauge stakeholder sentiment, then used AI to quickly analyze and categorize the responses.
• I created a job-aid on how to customize a navigation bar in a new system. I used AI for the first draft and formatting.

I have even used AI to do more sophisticated tasks. For example, AI helped me conduct a Segregation of Duties exercise during a major SAP implementation, identifying conflicting roles within jobs. This supported the client’s regulatory compliance. It also helped them to reduce the risk of fraud, error, and misuse of sensitive systems.

AI is not replacing change management. It is enhancing it, helping us deliver smarter, faster, and with greater confidence. At Emerson, we do not chase shiny objects. We use tools that help people adopt change and make it stick. AI is now one of them.

Onboarding during mergers or acquisitions means behavior change and culture alignment.

Mergers and acquisitions (M&As) are high-stakes transitions that test not only a company’s financial and strategic chops, but its ability to lead people through change.

The success of the integration hinges less on balance sheets than on behavior—how quickly and effectively employees adapt, align, and re-engage under a new banner. This is where onboarding (usually a tactical HR event) becomes a powerful and transformative process.

Behavior change starts with meaning.

In M&A environments, employees often feel like change is being done to them rather than with them. The first step in onboarding post-merger is restoring a sense of meaning.

Skip the boilerplate mission statements and strategic advantages. Instead, draw a clear throughline from the business rationale to employee realities. Don’t just talk about what is changing, but why—and what it means for employees’ roles, impacts, and growth.

How to do it: Smart organizations embed the merger story into onboarding touchpoints—town halls, manager one-on-ones, digital welcome kits—so that employees don’t just hear the change narrative, they begin to see themselves in it. That emotional engagement is the first step to the behavior changes you need.

Make the invisible visible.

One of the most common pitfalls in post-M&A onboarding is assuming culture will take care of itself. In reality, cultural alignment is a heavy lift.

Employees are often caught in a tug-of-war between legacy norms and new expectations. They need help decoding which behaviors are being carried forward, which are being left behind, and what’s new.

How to do it: Make the norms explicit—what you want employees to stop, start, and continue. One way is to use behavior charters or culture handbooks—not as static PDFs, but as conversation tools and performance rubrics.

For example, if the new organization values cross-functional collaboration, boil that down into observable employee behaviors: meeting and communication practices, decision-making rules, etc. Then reinforce those behaviors in real time (meetings and emails) and during milestones (performance reviews and reward practices).

Use peers and informal networks.

Formal onboarding only goes so far. Peer dynamics—who people talk to, learn from, and emulate—are among the strongest drivers of culture adoption. Post-merger onboarding should intentionally activate these social systems.

How to do it: Assign culture ambassadors or integration buddies, especially for employees moving from an acquired organization. And make sure they aren’t just tour guides—they’re behavior models.

Equip managers to lead the shift.

Middle managers are the linchpins of M&A onboarding, yet they’re often overlooked or underprepared. They’re expected to drive performance while managing uncertainty and modeling new behaviors themselves. Treat manager enablement as part of the onboarding process. A well-prepared manager can turn confusion into clarity and resistance into readiness.

How to do it: Equip managers to be their team’s first, best lifeline. This might include targeted coaching, just-in-time toolkits, or structured sessions on topics like navigating ambiguity or giving feedback across cultural lines.

Storytelling is another powerful way to transmit cultural DNA and reinforce behaviors. Help managers tell success stories about employees who demonstrate the “new way” of working—especially when they span legacy boundaries. These narratives don’t just reinforce desired behaviors; they signal what’s possible and safe within the new organization.

Measure and iterate.

Finally, onboarding should not be a one-and-done event—it should be a strategic, evolving process.

How to do it: Establish metrics that go beyond completion rates. Look at engagement levels, behavior adoption, time to productivity, and pulse feedback on cultural alignment. Then use those insights to refine the experience continuously.

In M&As, onboarding is not just about teaching systems and policies—it’s about shaping mindset and behavior. By designing onboarding as a deliberate culture transfer and behavior change effort, organizations can accelerate integration, reduce attrition, and build a new shared identity that’s greater than the sum of its parts.

Want to explore this topic in more detail or learn more about Emerson? Hop on his calendar: Book a meeting with Rich

Vacation prep might just hold the secret to better change management.

I’m currently planning a trip to England and let me tell you: I am very excited. I’m dreaming of long pub lunches (what keto diet?), exploring all of the Liverpool Beatles landmarks, and a tour of Anfield stadium (home of my beloved Liverpool Football Club).

But something struck me the other day as I was researching places to stay and planning my itinerary.

I realized that the anticipation of this trip might be giving me more joy than the trip itself will. Not because the trip won’t be amazing. (It absolutely will; I will be hitting numerous bucket list items.) It’s because my brain is already cashing in on the excitement. This is not unique to me, it turns out, but rather a well-researched phenomenon.

The Science of Looking Forward

A 2010 study published in Applied Research in Quality of Life found that vacationers often experience the highest levels of happiness before their trip even begins. The act of planning, imagining, and looking forward to something positive can create a sustained boost in mood — sometimes more so than the event itself.

Why? Because our brains love a good story, especially when we get to be the hero.

Anticipation activates the reward centers in the brain, creating a feel-good feedback loop.

We imagine the best possible version of the future; in doing so, we start to feel like it’s already happening.

Now here’s where it gets interesting: what if we could apply that same insight to one of the most notoriously stressful things in the workplace: organizational change?

Change Management Could Use a Holiday

Let’s be honest: when employees hear about a big change coming — a new system, a reorg, a shift in strategy — their first reaction is rarely joy. More often, it’s fear, resistance, or confusion.

But what if we could turn that reaction on its head by borrowing some principles from the psychology of vacation anticipation?

Here are five takeaways from the research on pre-vacation happiness that can be directly applied to leading people through change:

1. Build positive anticipation.

Just as a countdown to a trip builds excitement, leaders should start building positive anticipation early. Describe the better future in vivid, emotional terms. Make the outcome feel worth looking forward to — not just logical or necessary.

2. Involve people in the planning.

Part of the joy of travel is choosing your own adventure. Give employees a sense of agency by inviting them to shape how the change rolls out. When people feel like co-creators instead of passive recipients, engagement skyrockets.

3. Offer previews and sneak peeks.

Travelers love photos, reviews, and sample itineraries. In the workplace, you can provide early demos, pilot programs, or walkthroughs to help people visualize what’s coming. Let them mentally “try before they fly.”

4. Map the journey.

Much like a travel itinerary, breaking the change down into clear, manageable steps helps people feel oriented and in control. Celebrate milestones along the way. Give people a roadmap that makes the change feel achievable.

5. Support the post-trip dip.

Just as travelers often feel a slump after returning home, employees may feel underwhelmed or disoriented once a big change is implemented. Don’t let the momentum die. Continue telling success stories, offering support, and reinforcing the new reality.

Your Next Change as a Journey

If you’re leading change, you’re not just managing logistics — you’re guiding an emotional journey. Think like a travel agent. Stir excitement. Tell a compelling story. Help your people pack their bags for success.

Because if planning a trip can make someone happier than the trip itself, imagine what that kind of anticipation could do for your next change initiative.

Now if you’ll excuse me, I have to go find out whether cream or jam goes first on a proper English scone. (Spoiler: it’s a heated debate.)

Want to explore this topic in more detail or learn more about Emerson? Hop on his calendar: Book a meeting with Rich

If change management stalls, balance fuel and friction.

We’ve all seen promising change initiatives falter. We craft compelling visions, highlight the benefits, and try to generate excitement – we fill up on the “fuel”. But often, progress stalls even with a full tank. Why?

Loran Nordgren, Professor of Management and Organizations at Northwestern’s Kellogg School of Management, has tackled this conundrum. Nordgren is a behavioral scientist whose research explores the psychological forces that propel and prevent the adoption of new ideas.

According to Nordgren, we often focus too much on “fuel” and overlook the powerful forces resisting change: the “friction.”

What is Fuel?

Fuel is anything that increases the motivation or desire for change:

• Painting inspiring visions of the future state.
• Highlighting the urgency or benefits (the “why”).
• Offering incentives, recognition, or appealing rewards.
• Showcasing strong leadership endorsement.

We naturally focus here – trying to propel people towards the new goal.

What is Friction?

Friction comes from the psychological and practical barriers that make change harder, even if people are motivated – the forces that inhibit the change. These include:

• Effort: The sheer work required to adopt the new way.
• Complexity: Confusing processes or unclear instructions.
• Ambiguity: Uncertainty about roles, expectations, or outcomes.
• Emotional Costs: Fear of failure, loss of status, or breaking old habits.

These frictions act like headwinds, slowing down or stopping change entirely.

In his book, The Human Factor, Nordgren provides the example of a company that was struggling to sell innovative and customizable furniture despite great engagement and excitement from their target demographic. They added fuel to their initiative by doubling down on their brand’s unique offerings and even lowering prices. Sales remained static.

Pivoting to friction, they discovered the main hurdle was customers not knowing what to do with the furniture they would be replacing. Once the company started offering free removal services upon delivery, sales took off. It wasn’t a fuel issue; it was about removing unseen friction.

Find the balance.

Reducing Friction is often far more effective than adding Fuel. It’s easier to clear the path than to constantly push people harder down a rocky road.

Instead of focusing only on motivating (adding fuel), actively seek out and eliminate the frictions holding them back. Here’s how:

• Identify the frictions. Ask: What makes this change difficult for people? Where is the confusion? What old processes are getting in the way? What anxieties exist?
• Simplify ruthlessly. Make the desired new behaviors as easy as possible. Streamline processes, provide clear templates, offer step-by-step guidance.
• Clarify and communicate. Reduce ambiguity. Ensure roles, responsibilities, and expectations are crystal-clear. Address concerns directly and honestly.
• Provide support. Acknowledge the emotional effort involved. Offer training, resources, and easy access to help.

Effective change management isn’t just about selling the destination; it’s about paving the road. By shifting focus to identifying and removing the barriers, you make change smoother, faster, and more sustainable.

Engage your non-tech-savvy workers during a supply chain transformation.

In today’s digital landscape, supply chain transformation isn’t just a tech upgrade—it’s a people-centric revolution. As companies modernize their operations and integrate state-of-the-art systems, they often face a challenge: how do we empower seasoned employees who might not be as comfortable with technology? Here are some essentials to reduce digital friction and enhance adoption.

Honor their expertise.

Non-tech-savvy workers are the backbone of your organization. They often understand the intricacies of operations better than anyone else.

Frame their engagement in your digital transformation as tapping into a well of their practical insights.

Because that’s what it is. You need the input and adoption of employees – especially those “on the ground.” So, rather than framing digital transformation as a stark departure from the ways they’ve made your company successful, position it as an evolution that builds on their expertise. This is a collaboration, so it must be based on mutual respect and shared goals.

Tell the right stories.

Sometimes, the best way to inspire involvement is by sharing success stories. Highlight case studies—both from within your organization and from others in your industry—where similar transformations have boosted efficiency and enriched the work experiences of team members.

Tell the story of a journey toward group success rather than an imposition of new rules and technology.

For example, when a manufacturing unit introduced an intuitive inventory management system, their veteran workers hesitated, but they eventually became the system’s biggest champions. How? Their real-world insights led to iterative improvements that made the tool more user-friendly for everyone. Telling real stories like that gives hope and validates the efforts of every worker involved.

Speak their language.

One of the most daunting aspects for employees who are not digital natives is the jargon. A lot of the complex language is just unnecessary. Transforming this narrative starts with simplicity:

Use relatable language. Avoid overly technical terms. Instead, explain connections between new systems and familiar tools or everyday processes.

Create visuals and demonstrations. Use diagrams, flowcharts, or even analogies from everyday life to illustrate how a digital tool will fit into their normal workday.

Break it down. Provide clear mini-guides or ‘cheat sheets’ that walk users through system functionality in bite-sized pieces. Work with the employees on the ground to develop make sure the cheat sheets use the right language.

Don’t forget the WIIFM. When you’re talking about the “why” of the new system, think from the employee’s point of view. Of course, the organizational strategy will be served, but how will the change make the work better – easier, more interesting, more impactful, or safer? Safety is a big part of the culture in industries like Manufacturing and Energy. Talk about how the new technology mitigates inherent risks like driving, working at heights, or working with heavy machinery.

By demystifying the technology, you turn it into a tool for empowerment instead of a barrier to engagement.

Train them effectively.

Non-tech-savvy workers don’t need a one-shot, super technical, intense session. They need a longer runway and an experience that makes sense to them. They need custom, personalized training and continuous learning opportunities.

Use trainers who know the work. Ask your functional subject matter expertise to identify employees who would make great trainers. People appreciate learning from their colleagues, not consultants. Spend adequate time training the trainers.

Build training around their job roles. Learning should happen in the context of their real job functions, so use realistic scenarios to set up demonstrations and practice activities. And teach only what they need. For instance, while managerial staff might need to understand analytics dashboards, shop-floor employees need to learn the functionality they need to keep the operation running.

Give learners a taste of success. Let users “play in the system” during training, using realistic scenarios and activities. Then, use a “sandbox” environment to allow them to practice after training and before go-live; they’ll get a better feel for the new ways of working.

Foster mentorship. Pair less digitally inclined workers with tech-savvy peers. This not only accelerates the learning curve but also builds camaraderie across generations and skill sets. And it gives the worker an on-demand source of support. Speaking of which…

Create on-demand resources. Workers can’t easily get to the performance levels you need inside a training session. They will continue learning on the job. So, give them easily accessible video tutorials, FAQs, job aids, and peer experts they can use and revisit at their own pace.

Support the real work after go-live. Make sure you have a support process in place. Where do folks go when they need help? Are they reaching out to the project team? Should they go to the helpdesk? What’s the process for submitting issues? Build the support system and answer all these types of questions.

By continuously supporting learning and offering multiple avenues of engagement, transformation becomes accessible—and even exciting.

Keep talking.

A successful transformation is built on two-way communication. Encourage your team to share their experiences, challenges, and their small wins with the new system. Here are some ideas.

Schedule regular check-ins. Schedule informal roundtable sessions or “digital clinics” where employees can voice concerns, practice new skills, and even suggest improvements. Set up lessons learned sessions or retrospectives to allow users to talk about things they’ve learned OR ways to do things better the next time. This is especially important when you’re doing multiple phases or rollouts.

Reinforce their progress. Celebrate milestones, whether it’s trying an online activity for the first time, completing training, mastering a new feature, or hitting a team performance metric. Every organization “celebrates” differently. Find out the best way to recognize your employees. For some organizations, it could be a certificate. Other organizations appreciate cold, hard cash! What works in your organization? The right recognition can transform apprehension into pride.

Use feedback loops. Solicit employee input to refine functionality, communications, training, and support resources. When workers see tangible changes stemming from their feedback, it reinforces their sense of ownership and trust.

Create an environment for your next success.

At its core, a supply chain transformation is about synergy. Create an environment where every employee, regardless of their technological proficiency, feels included in innovation.

Encourage cross-functional teams. Blend experienced non-techie workers with digital experts to work on projects together. That kind of diversity promotes broader perspectives and better problem-solving.

Invest in change leadership. Identify and empower internal ambassadors or “change champions”: who believe in the digital vision and can help bridge the gap. These leaders will naturally grow into mentors and drive motivation across the ranks. As you do, be mindful of culture and pick the right influencers. For example, first-line supervisors are the key to getting the masses on board in some organizations. Be realistic; sometimes the shop floor needs to hear a message from their direct supervisor, not someone from corporate HQ or even a respected peer.

Foster a culture of collaboration. Beyond formal training sessions, organize informal events or ‘lunch-and-learn’ sessions that naturally encourage sharing and learning.

A collaborative environment transforms the transformation project from a top-down mandate into a collective, inclusive mission.

Supply chain transformation is an opportunity to reimagine not only your processes but also the very fabric of your organization. By engaging non-tech-savvy workers and valuing their experiences, you can make your digital evolution inclusive, effective, and sustainable. Remember, transformation is not merely about installing new software; it’s about enabling the entire organization: people, process, and technology. Let’s bridge that digital divide and make sure everyone is part of the digital future.

Want to explore this topic in more detail or learn more about Emerson? Hop on his calendar: Book a meeting with Rich

Reflections On Earning My PMP.

I didn’t earn my Project Management Professional (PMP) certification because I aspired to be a project manager.

My background is in change management—the people side of transformation. I help individuals and organizations navigate uncertainty, build confidence in new ways of working, and ultimately adopt change that lasts.

But as I supported more large-scale initiatives, I noticed a pattern: the best change efforts had strong project management. I wanted to deepen that alignment—not just to speak the language of project managers, but to truly understand their priorities, tools, and pressure points. That’s what led me to pursue my PMP.

The project plan meets the people plan.

Studying for the PMP felt like stepping into a parallel universe—full of frameworks, formulas, and flowcharts.

But the more I learned, the more I saw connections. Work Breakdown Structures? They help change managers identify where resistance might emerge. The stakeholder register? A goldmine for mapping influence and engagement. Risk management plans? They’re just as valuable for adoption risk as they are for scope creep.

The structured approach of project management doesn’t replace the human-centered approach of change management—it enhances it.

Acronyms blur and dogs bring clarity.

There was a moment during my PMP prep where I hit a wall. The acronyms—WBS, RACI, EVM—were swirling, and I couldn’t see the forest for the formulas. That evening, I took my dog Stella for a walk and let my mind wander to a tech rollout I was helping lead. The project plan was solid—timelines were clear, deliverables scoped, dependencies mapped.

But adoption was stalling. Users were confused about what was changing, some hadn’t attended training, and support requests were already coming in. That’s what we mean when we talk about adoption: not just whether the tool is live, but whether people are actually using it as intended, with clarity and confidence.

That’s when it clicked. This PMP certification wasn’t just about passing a test—it was about bridging a gap. I saw how the tools in the PMP—like stakeholder analysis, communication planning, and risk response strategies—could help me be a stronger partner on the people side. I could spot where the rollout might cause disruption, ask better questions during planning (like “How will this impact workflows?” or “Who might resist this and why?”), and help teams proactively manage resistance instead of reacting to it.

That shift—from reacting to anticipating—is where real change starts to take root.

The heart of a PMP is still human.

Yes, the PMP is built around processes, deliverables, and control. But at its core, it’s about clarity, collaboration, and outcomes. These are also the foundations of great change management. Earning this certification didn’t change who I am—it expanded how I think.

Fellow change managers: this is your sign.

If you’ve ever wondered whether the PMP is worth your time as a change professional, I’ll say this: it won’t make you a different kind of practitioner, but it will make you a deeper one. It’s more than passing an exam. It’s about building bridges—between planning and adoption, strategy and empathy, people and process.

Because when those elements move together, that’s when change truly sticks.