Unlocking Corporate Learning with AI Simulations

Bottom Line Up Front: In this article, you’ll learn about recursion—a powerful concept of breaking down complex problems into simpler, repeatable steps—and how it mirrors the use of AI-driven simulations in corporate training. You’ll also understand how to effectively design and utilize AI simulations to help learners practice essential corporate skills.

It begins with a box.

Imagine holding a large box. Within it, another box rests snugly. Inside that, yet another. This continues, box within box, like nested dreams, until finally, you open the smallest, innermost container—only to find it empty. This is recursion, an elegant dance of simplicity and complexity intertwined.

Yet, suppose a note had been hidden within one of these boxes. Your task becomes clear yet mysterious: open each box, peer inside, and ask, “Is this the one with the instructions written on it?” If the answer is no, you move deeper into the nested layers. But if the answer is yes, your search concludes triumphantly by reading those instructions and doing the task. Recursion, then, is not merely repetition—it’s thoughtful repetition, each step moving you intentionally closer to resolution.

This idea of recursion—breaking complex problems down into simpler, repeated steps until clarity is found—directly parallels how AI-driven simulations function. AI simulations similarly take a complicated learning objective and break it into clear, manageable interactions, guiding users steadily towards deeper understanding and mastery. The empty box is your base case, signaling it’s time to stop. Every other box represents your recursive case, compelling you onward with instructions until you accomplish your goal. The real beauty of recursion lies in its ability to simplify complex problems, breaking them down into manageable parts while maintaining a clear path to the solution.

This simple, vivid analogy helps illuminate a more intricate and profound use of AI—creating simulations for meaningful practice in a corporate environment.

As I’ve shared before, prompting AI resembles an ongoing dialogue, a thoughtful exchange rather than mechanical command-giving. Crafting an AI-driven simulation involves precisely this kind of conversation—an iterative dialogue where thoughtful questions and responses gradually guide AI toward generating meaningful, tailored experiences. Here, AI serves as both Game Master and Mentor, setting scenarios for students or employees to practice crucial skills—whether negotiating, hiring, or pitching ideas.

Here’s how such a simulation unfolds:

The AI mentor begins with clarity and friendliness, introducing itself warmly: “I’m your AI mentor, here to help you practice negotiations (or hiring, or pitching—whichever the instructor chooses).” I have used this prompt to teach me several advanced Enterprise Architecture skills. You then tell the AI about your experience with this topic and your background so it can create the ideal scenario for you. The mentor waits patiently, adapting its response thoughtfully based on the participant’s reply, just as it did for me when guiding my salmon-cooking adventure.

Once the mentor understands the user’s needs, it offers three distinct scenarios, each crafted to engage and challenge participants uniquely based on their individual skill levels and the topic in question. Imagine one scenario unfolding in the boundless vastness of outer space, another deeply grounded in the realities of organizational dynamics, and yet another perhaps within an unusual yet enlightening context. Choice empowers the participant, echoing the ideas I shared in how I shaped the outcomes I needed as a Cub Scout leader,where thoughtfully designed options facilitated meaningful growth.

Upon selection, the mentor provides precisely what participants need—no more, no less—ensuring clarity without overwhelming complexity. “BEGIN ROLE PLAY,” it declares, setting a scene rich with detail and narrative depth, inviting participants into their roles compellingly and naturally.

Through six conversational turns, the AI remains steadfastly in character, prompting participants toward decisions of significance and consequence. The decisions aren’t arbitrary; they’re designed to challenge participants on key learning outcomes. Then comes a pivotal moment, a meaningful choice that crystallizes learning and concludes the simulation.

“END OF ROLE PLAY,” the mentor announces gently but clearly, transitioning seamlessly into feedback. The critique balances encouragement with insightful recommendations, tailored precisely to participants’ goals, performance, and growth areas. This constructive dialogue fosters ongoing development, anchoring learning firmly in practical, reflective advice.

As the AI creates the instructions to execute the simulation, it uses recursion by breaking down the instructional steps into smaller, repeatable actions. The instructor sets the overall course, the student experiences the role play, and the AI responds to the student’s input through bite-sized questions to craft scenarios rich in meaning:

• What specific skill or concept do you wish to teach?
• What are the essential elements students must grasp?
• Where do students typically stumble or misunderstand?

With each interaction, we delve deeper into understanding, carefully structuring the simulation to match educational intent precisely. The AI reminds the individual constructing the course: “The more context you share, the better the scenario becomes.”

Ultimately, AI-driven simulations serve as elegant recursive explorations themselves—each interaction building upon the previous, guiding participants through layers of learning until they reach the insightful “empty box” of understanding. It’s a process of thoughtful iteration, shaping not merely skills, but comprehension, empathy, and wisdom.

Just as recursion is both a practical method and a philosophical concept, using AI in this deliberate, reflective manner illuminates deeper truths about how we learn, teach, and grow. AI, thoughtfully prompted, becomes more than a tool—it becomes a partner in our perpetual quest for meaningful understanding.

So, what scenario would you design today, and what hidden note might your learners uncover within it?

Below is a prompt you can use to create your own AI-driven simulations, helping users master essential corporate skills.  Make sure to copy and paste this prompt into Copilot for Web, and to follow the instructions.  It will finish by spitting out a huge prompt, that you can then put into another prompt with Copilot, which will then use to role-play out a simulation where you can gain new skills.

https://tedt.org/prompts/Simulation-Creator.md