Preparing Your People for AI: It's Never About the Technology

Author

Charlene Li
April 28, 2025

In all my years studying digital transformation, I've learned one fundamental truth: you think it's about the technology—but it's never about the technology.

It's always, always, always about the people.

This is even more true with AI, which may be the most transformative technology we've seen in our lifetimes. While everyone's excited to play with models and agents and no-code tools, the real challenge is setting those technologies aside and focusing on the human element: how people will use these technologies and how their work will change.

The organizations that win with AI won't be the ones with the fewest human employees (though that's a tempting conclusion). They'll be the ones with the most capable human employees who know how to use these tools.

Moving Past Fear to Trust

Before your team can become "superhuman" with AI, they need to move past fear. A recent Stanford study revealed that, while 83% of people in China and other Asian countries are optimistic about AI’s benefits outweighing its risks, only 39% of Americans feel the same way.

This fear isn't just among the usual suspects. It's not only older employees or the technologically hesitant who are anxious. I'm hearing concerns across all age groups, demographics, roles, and education levels—from young people concerned about sustainability to experienced managers worried about their relevance.

Here are the fears I hear most often:

"I won't have a job next year." 

"My years of experience won't matter anymore." 

"This is just another change initiative that leadership will abandon." 

"AI is being forced on me rather than something I have control over."

These fears are valid, and they must be acknowledged before you can build trust.

Building Trust Through Transparency

To overcome these fears, leaders need a radically different approach to change management:

1️⃣Be transparent about what's changing and why

This isn't the time to beat around the bush. If you don't have a coherent AI strategy that you can clearly articulate, your employees' anxiety will only grow. They need to know: Why is the organization pursuing AI? Is it just for efficiency, or is there a more compelling strategic reason?

Set clear expectations and boundaries about where AI will and won't be used. Be as specific as possible about focus areas, timelines, and impact.

2️⃣Communicate often

One of the biggest mistakes in change management is not communicating frequently enough. The same message needs to be repeated: "This is where we're going. This is why we're going there. This is how we'll get there. This is the impact on you."

3️⃣Acknowledge what you don't know

With AI, there's a lot we're still figuring out. Being transparent about uncertainty builds more trust than false certainty.

4️⃣Create safe spaces for feedback. Employees need a container where they feel they can share concerns without judgment. Listen truly, without dismissing fears.

One large global organization we interviewed took this approach. They identified three groups: enthusiasts (early adopters racing ahead), a "cautious neutral majority" (most employees), and skeptics (those with deep concerns). They focused especially on demystifying AI for the skeptics, breaking it down into practical applications to lower the temperature in the conversation.

The organization also trained leaders not just on technology but on creating psychological safety—giving them tools to listen to concerns, understand different groups' perspectives, and normalize uncertainty. This was crucial because our typical workplace culture rarely makes time for conversations about ambiguity and uncertainty.

Reimagining AI Training

AI fluency requires two sets of skills: AI collaboration skills and critical human skills.

AI collaboration skills include effective prompting, evaluating output, iterating to refine results, and determining which tasks to delegate to AI. These are the technical aspects of working with AI tools.

But equally important are critical human skills: exercising good judgment, ethical reasoning, creativity, social intelligence, and complex problem-solving across functions. These are the capabilities that make us uniquely human.

Traditional training approaches won't work for developing these skills. No lecture or one-time workshop can build the judgment and discernment needed to work effectively with AI. Instead, we need a fundamentally different approach to AI training:

  • Training can't come from on high. It can't be something IT or HR develops in isolation. It must be a shared responsibility across departments and with the learners themselves.

  • Start with practice, not theory. Get to the nuts and bolts quickly: "This is the problem. This is how to solve it. This is your task. This is how to use AI."

  • Teach evaluation, not just execution. Help people recognize what "good" looks like and how to improve results.

  • Encourage informal peer learning. Some of the most effective training happens when colleagues share discoveries over lunch or in Slack channels. Support this organic, continuous, peer-based learning.

  • Reward mindset, not mastery. I don't know what it means to "master" AI—I'm constantly discovering new applications myself. Instead of expecting perfection, reward curiosity, creativity, and the willingness to experiment.

IKEA provides an excellent case study for this approach. They created role-specific training across their global workforce. All co-workers received fundamental AI skills for daily tasks, ethical boundaries training, and output evaluation skills. Those in specialized roles received deeper training specific to their workflows. Leaders participated in "AI exploration days" where they saw strategic applications in action, while tech teams received detailed technical instruction.

This tiered, practical approach acknowledges that one size doesn't fit all. Training must be tailored to specific roles and needs.

Leading Hybrid Human-AI Teams

As agentic AI becomes more prevalent, leaders face a new challenge: managing teams of both humans and AI.

The evolution is happening in stages:

  1. AI as a tool (where we are today)

  2. AI as a collaborator (working side by side)

  3. AI agents working independently within boundaries

  4. AI orchestrators directing workflows (of both other AIs and humans)

This progression requires us to develop new leadership capabilities:

  • Setting goals that both humans and AI understand 

  • Defining clear boundaries of autonomy 

  • Designing processes that integrate human judgment 

  • Creating space for uniquely human capabilities like creativity and empathy

The future belongs to leaders who can orchestrate these hybrid teams, knowing when to leverage AI and when to rely on human strengths.

Measuring Success

How do you know if your efforts to prepare people for AI are working? Look for these indicators:

  • Trust and readiness. Are employee surveys showing improved sentiment toward AI? Are people voluntarily adopting these tools? Is there grassroots sharing of best practices?

  • Skills development. Are employees demonstrating proficiency in using AI effectively?

  • Business impact. Are you seeing productivity gains, quality improvements, and employee satisfaction?

  • Agent performance. As you incorporate AI agents, are they creating value or friction? How much oversight do they need?

The organizations that thrive won't be those that replace humans with AI, but those that empower humans to work alongside AI—creating teams of augmented workers who can accomplish what neither humans nor AI could do alone.

Your Turn 

How is your organization preparing employees for an AI future? What approaches have you found most effective in addressing fears and building trust?

If this information was helpful, there’s plenty more!

What I Can’t Stop Talking About 

  • Bridging the AI knowing-doing gap. Is your C-suite stuck in AI limbo? Unless leaders are actively using AI themselves, they can't effectively lead their organizations into the future. Many executives understand AI conceptually but aren't hands-on users. Here’s a practical guide to move your leadership from AI-aware to AI-empowered. 

  • The promotion paradox. One of the most dangerous career moves isn't staying put—it's accepting the wrong promotion. I learned this the hard way.  Organizations too often equate management with advancement while failing to support people who excel as individual contributors. Here, I’m asking, what if we normalized returning to previous roles without stigma?

  • The 9s vs 4s framework. In any organization, there are exceptional performers (9s) and adequate ones (4s). With 9s, my approach is clear: get out of their way and let them soar. With 4s, I ask one critical question: could they become 9s? Here’s what to do when you find out. 


📌 Join me and Andreas Welsch on May 8th for a candid discussion where we'll discuss agentic AI and break down the hype and explain what decision-makers need to know about this rapidly evolving space.

📌 Sign up for updates and early access to my upcoming book, co-authored with Katia Walsh, which is all about creating a winning AI strategy.

📌 Take my latest LinkedIn Courses! 

→ “The Manager's Guide to Integrating and Managing AI Agents." In this brand-new course, I offer practical approaches for effectively managing both AI agents and human employees as a unified team. Ready to lead with confidence? Get the course here.

→ "Transforming Business with AI Agents: Autonomous Efficiency and Decision-Making." I provide a comprehensive introduction to autonomous AI agents, explaining how they differ from other AI products, boost productivity, and enhance decision-making while addressing key ethical considerations. Explore the course here.

→ You can also review the slides and recordings of two of my all-time favorites, “Unlocking The Power of Generative AI,” and “Developing a Winning Generative AI Strategy for Competitive Advantage.”

My Upcoming Appearances

Charlene Li

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