This is now the first question asked at nearly every business acumen simulation workshop we
"Are we allowed to use AI?"
The answer surprises people.
Yes.
And no.
For context, our business simulations are not connected to AI. Participants never have access to the underlying simulation engine, the algorithms, or the calculations that determine the business results. They cannot ask AI for the "right answer" because the AI has no access to the actual simulation model.
Participants can copy and paste information from reports, dashboards, financial statements, market research, and operational data into an AI assistant to request guidance, coaching, recommendations, or explanations.
In other words, AI can help them think. But AI cannot do the work for them.
At least not yet. What has fascinated me over the past six months is watching how different teams use AI and how dramatically the outcomes vary. Some teams become smarter, faster, and more strategic. Others become dependent, disengaged, and surprisingly ineffective.
The experience has convinced us that the real question is not whether AI should be allowed in learning environments.
The real question is whether people know how to use AI without surrendering their own judgment.
Based on what we have observed and measured across hundreds of participants, here are five reasons to allow AI into business simulations…and five reasons to be cautious.
The Pros
1. AI Accelerates Learning
Business simulations often expose participants to concepts they may not use every day: pricing strategy, working capital, shareholder value, operating margins, cash flow, inventory turns, and return on investment.
Traditionally, participants spend a significant amount of time simply trying to understand the terminology before they can begin making decisions.
AI dramatically shortens that learning curve. Instead of spending twenty minutes figuring out what a metric means, participants can get a clear explanation in seconds and spend more time discussing strategy, trade-offs, and business decisions.
The result is often deeper learning, not less.
2. AI Encourages Curiosity
Many participants are reluctant to ask questions in front of colleagues, senior leaders, or subject matter experts.
Nobody wants to be the person who asks what EBITDA means.
AI creates a judgment-free environment where people are willing to ask questions they might never ask in a classroom. The result is often more exploration, more experimentation, and a greater willingness to engage with difficult concepts.
3. AI Creates a Personalized Coach
One of the most interesting observations we've made is how frequently participants use AI as a private executive coach.
They ask questions like:
When used this way, AI becomes less of an answer machine and more of a thinking partner.
And that's where some of the real value begins to emerge.
4. AI Expands Strategic Thinking
The best teams rarely ask AI for answers. Instead, they ask for alternatives.
They use AI to challenge assumptions, identify blind spots, explore different stakeholder perspectives, and think through second- and third-order consequences.
The quality of the discussion improves because the number of ideas being considered expands dramatically. In many cases, AI enhances strategic thinking rather than replacing it.
5. AI Reflects the Real World
Let's be honest. The future workplace will not be AI-free.
Leaders, managers, salespeople, engineers, marketers, and finance professionals will increasingly work alongside AI assistants every day.
If our learning environments completely prohibit AI, we may unintentionally train people for a world that no longer exists.
Learning should prepare people for reality, not preserve the past.
The Cons
1. AI Creates the Illusion of Understanding
This is perhaps the biggest risk. Participants receive a polished, well-written recommendation and assume they understand it.
But understanding a recommendation is very different from understanding the reasoning behind it. AI can make people feel smarter without actually making them smarter.
The danger is confusing confidence with competence.
2. AI Can Short-Circuit Critical Thinking
Some teams stop thinking the moment AI provides a recommendation.
Instead of debating alternatives, challenging assumptions, and evaluating trade-offs, they simply follow instructions. Ironically, the teams that rely most heavily on AI often learn the least.
Business acumen develops through struggle, analysis, discussion, and decision-making—not through copying and pasting recommendations.
3. AI Can Reduce Healthy Team Conflict
Great business decisions often emerge from disagreement. Different viewpoints challenge assumptions and improve outcomes. But when AI becomes the authority in the room, discussions often end prematurely.
Someone reads the AI recommendation, and everyone nods. The debate disappears. Unfortunately, so does much of the learning.
4. AI Recommendations Are Often Generic
Business simulations are intentionally built around ambiguity, uncertainty, and trade-offs.
AI frequently generates recommendations that sound intelligent but fail to account for the unique circumstances of the situation.
The advice is often directionally correct but strategically incomplete. Participants still need judgment.
And judgment remains one of the most valuable leadership skills in business.
5. AI Can Become a Crutch
Perhaps the most concerning observation is how quickly some participants begin deferring responsibility to AI.
When the recommendation works, they take credit. When the recommendation fails, they blame the AI. Neither response develops leadership capability.
Leadership requires ownership. And ownership requires making decisions when certainty is impossible.
So What Should Organizations Do?
After observing teams across industries and regions, I have reached a conclusion that may sound contradictory.
Organizations should neither ban AI nor fully embrace it. Instead, they should teach people how to challenge it. The highest-performing teams are not the teams that use AI the most.
They are the teams that use AI the most intelligently. They ask better questions. They challenge recommendations. They test assumptions. They debate the outputs.
Most importantly, they retain ownership of the final decision. They understand that AI can inform a decision, but it cannot make a decision.
In other words, they treat AI as an advisor, not as a decision-maker.
And that may be one of the most important leadership skills of the next decade. The future will not belong to people who can outthink AI.
Nor will it belong to people who blindly follow AI.
It will belong to people who know when to trust it, when to challenge it, and when to ignore it altogether.
So I'll leave you with the same question I now ask executives at the end of our workshops:
If a team using AI consistently outperforms a team that refuses to use AI, which team is actually demonstrating better business acumen?
Last week, the average results of a cohort going through a custom simulation were up about 10% from the year before, and they swear it was because they leveraged AI.
The answer may tell us more about the future of leadership than we realize.