Everyone in the business acumen simulation workshop I conducted last week was using AI assistants to research data, understand reports, and make decisions.

Some teams performed better than others, and a couple were absolutely extraordinary.  They set all-time simulation records for stock price, revenue growth, profitability, and shareholder value.

Naturally, during the final debrief, I asked the top-performing team what they had done differently. I expected to hear something about strategy, financial analysis, or decision-making discipline.

Instead, one participant said something fascinating:

"We coached our AI agent much differently than we coached each other. The feedback and the way we communicated with the AI were much clearer and more clarifying, and it made a huge difference."

The room got quiet.

As we unpacked that statement, it became obvious that they had stumbled onto something profound. The skills required to coach AI effectively are surprisingly different from the skills required to coach people effectively.

In fact, in some ways, AI is exposing weaknesses in how we communicate with each other.

As we continued discussing it, something started to bother me.

For years, leaders have been taught that coaching is fundamentally a human skill. It requires empathy, trust, emotional intelligence, and the ability to adapt your communication style to different personalities.

Yet here was a team telling me that one of the reasons they were successful was that they coached an artificial intelligence tool more effectively than they coached each other.

The more we talked, the more I realized this wasn't really a conversation about AI at all. It was a conversation about communication. AI was simply exposing habits that have quietly crept into our workplaces for years.

We have become comfortable being vague. We assume people know what we mean. We avoid difficult feedback. We rely on titles and authority to drive action.

And because humans are generally pretty good at compensating for our communication flaws, we rarely notice the problem.

AI doesn't compensate. It simply gives us back exactly what we asked for. That realization led to five observations that I haven't been able to stop thinking about.

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What “Owning” the Work Really Means in the Age of AI-Enabled Leadership

One of the most interesting parts of my job is interviewing senior leaders from around the world and across industries to gather their insights so we can build realistic business leadership simulations that help organizations learn by doing.

Recently, as part of a new leadership simulation for a global professional services firm specializing in construction and project management, I had a fascinating conversation with one of their senior leaders.

Like many organizations, they are trying to develop stronger early-career and mid-level leaders. Their business operates in two worlds simultaneously. They must execute today's projects flawlessly while also building tomorrow's business through a pipeline of opportunities, customer relationships, and future commitments.

During our discussion, we began talking about accountability and ownership. The leader made a comment that really got me thinking about what he said and then about what I am seeing in the business world these days.

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For years, leaders have preached the same message:

Move fast. Break things. Experiment. Learn. Innovate.

In many of our business acumen and leadership simulations, we actually reward aggressive experimentation, rapid decision-making, and calculated risk-taking because, quite frankly, organizations that don’t innovate eventually become irrelevant.

But a recent conversation with a senior finance leader completely reframed part of my thinking.

I was interviewing the CFO of a massive, multibillion-dollar business unit as part of a strategic leadership simulation we are building focused on innovation, finance, and enterprise decision-making. During the conversation, he made a statement that was simple, direct, and honestly pretty brilliant:

“If everyone in the organization is breaking things in the name of innovation, eventually you run out of money to fix them.”

That landed hard.

Because he wasn’t arguing against innovation. He was arguing for something much more sophisticated:

Lowering the cost of failure while still encouraging breakthrough thinking.

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At ATD 2026, the annual Association of Talent Development conference, we invited attendees to step into the role of the executive leadership team inside a live business simulation challenge. No slides. No passive learning. No theoretical case study.

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Next week, thousands of learning and talent development professionals will gather at the ATD 2026
International Conference & EXPO in Los Angeles, the premier event in the talent development space. And if I had to make one overarching prediction about this year’s conference, it’s simple: AI will dominate nearly every discussion.  In fact, my five predictions for ATD this year are:

1. AI
2. AI
3. AI
4. AI
5. AI

The real challenge at ATD may not be finding AI. It may be finding something that doesn’t mention AI. AI has rapidly become the centerpiece for learning, leadership development, coaching, simulations, content creation, role-play practice, performance support, workforce transformation, and more across our industry.

But what I think is most interesting is how much the conversation has evolved over the past year. The early wave of AI adoption focused heavily on efficiency: creating content faster, reducing manual work, accelerating development cycles, and automating repetitive tasks.

Now the conversation is becoming much bigger. Organizations are increasingly looking beyond AI as simply a productivity shortcut and starting to ask how AI can actually help develop people, improve performance, accelerate readiness, strengthen decision-making, and build capability at scale.

In other words, the conversation is shifting from: “How can AI help us work faster?” to:
“How can AI help people perform better?” That is a fundamentally different discussion. So beneath the obvious “everything is AI” narrative, here are the five themes I actually expect to see and hear across the conference.

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