By Ben Rollenhagen and Ted Theocheung
Executive Summary
A magic trick has three parts. The "Pledge", where the magician shows something ordinary; the "Turn," where the magician makes it do something extraordinary; and the "Prestige," where the magician brings it back to its original state. The first encounter with an agentic AI training tool for most people is like watching a magic show. The initial release of agentic AI training tools captivated the attention of most instructional designers and instructors. The ability to have dynamic, conversational role-plays with an artificial intelligence felt like the future had arrived. It wasn't necessarily that the tool was effective, but the sheer novelty of it was breathtaking.
As the 'spell' wears off, many professionals in this space quickly realize these tools were not designed to create true educational improvements. Role plays are not implicitly built for learning: a relatively permanent change in behavior. Rather, they are only a small piece of the learning puzzle. Like a magic trick, the key to figuring out how it works isn't to watch the hand with the bird, it's to watch what the other hand is doing in the background. This is a learning and developmental blind spot that must be addressed. This 'magic' is the very illusion that countless ed-tech startups are currently selling to invigorate the corporate training space. They are marketing a new toy, a novel, conversational facade, while neglecting the fundamental principles of how humans actually learn.
The Current AI Role Play Experiences
One iteration of this magic of technology in education that is gaining in popularity and reach, is role play. Companies use role play to supposedly deploy high-fidelity, on-demand simulations where employees engage in complex, live conversations with "virtual humans" or AI agents. These agents are powered by an advanced technology often referred to as Agentic AI, meaning they are autonomous and goal-driven. The goal is to make the experience as close to a real-life interaction as possible, complete with unpredictable responses. The intention behind agentic AI role playing has moved far beyond simple chatbots, focusing on creating highly realistic, dynamic conversational practice environments.
Here are some examples of role play scenarios:
Sales Teams: Practice handling difficult objections, mastering cold calling techniques, and refining pitch delivery.
Customer Service: Practice managing high-stress customer complaints, demonstrate empathy to improve efficiency and customer satisfaction.
Management: Practice difficult conversations, like coaching employees or delivering constructive feedback.
The role play simulations work because the AI agent is not constrained by a fixed script. Instead, the AI agent is autonomous; it has its own objective (e.g., a "virtual customer" whose goal is to save money) and can reason and adapt its responses in real time. Here are two main benefits of role plays:
Dynamic Responses: If the learner performs well, the AI may proceed smoothly. If the learner makes a mistake—say, they sound aggressive or fail to answer a question correctly—the AI can autonomously change its strategy, perhaps becoming skeptical or "pushing back" on the learner, forcing the learner to pivot and adapt immediately, just like a real conversation.
Objective Feedback: Instead of waiting for a human coach, the AI system uses advanced analysis (including looking at the sentiment and emotional tone of the responses, not just the words) to provide immediate, objective scoring and feedback. This helps the employee know exactly what they did right and wrong the moment the conversation ends. It also saves the company time compared to the time and experience required to set up in-person role plays.
The Opportunity
The issue here is that without the fear of consequences or accountability, the brain won't respond and the skill will be learned to be used in that safe setting. Failing in a safe space is great for learning new skills or practicing, but learners need that stress and anxiety and fear of failure, or real consequences, for learning to be stored deep and saved for the future. It's what re-wires the brain most efficiently and effectively. In practice, if an employee fails, they lose the sale. Sure, learners should BEGIN the learning process in a safe, comfortable environment with no real failure, but as soon as they are ready, they should start practicing their new skills in progressively more challenging situations and realistic scenarios, with real consequences. Ideally, the first time they see a real challenge shouldn't be with a live customer!
For a learner to change behavior, a learning experience must require the learner to truly apply knowledge in "unpredictable, unkind, or open settings" (phrases used to describe the messy reality of the real world), they need to build confidence and competence. Like a football team playing 'crowd' noise in a stadium, some companies try to overcome this with gamification, or a points system. These and other external motivators are good in short-term bursts, but they lack long term effectiveness. Learners need to be motivated internally. To do this, they need to see that what they have learned works and the work they put in is worth it. In essence, current tools fail at this because they ignore key learning science principles like Cognitive Load Theory and Self-Determination Theory.
The Difficulty with Data
Many role play companies are great at collecting and projecting data and results for the learners. They do a great job letting them know what the learner did wrong and what can be improved. These metrics are what most companies use as their moat (short for "economic moat"). Moat refers to a term, popularized by Warren Buffett, for a company's durable or sustainable competitive advantage that makes it difficult for competitors to erode its profits and market share over time. Right now, companies are designing new methods to collect unique data in order to stand out from the role play crowd.
Whether they are unique or not, every other company is collecting data in these main categories: Engagement and participation rates, Completion rates, Frequency of use, Sales rep performance, Sales KPIs, and Onboarding time.
While this data might be good for the company, it has no value to the learner if they can't use it. Knowing what you did wrong and having repeated opportunities to practice, refine, and improve with ongoing feedback is critical to the learning process.
This is something Mentor126.ai is intentionally designed to do. The primary goal of high-fidelity AI simulations is not just data collection, but to close the loop between assessment and immediate action. Without dynamic remediation, assessment data remains a retrospective report. Agentic AI is engineered to transform evaluation from a diagnostic tool into a proactive, co-regulatory intervention, ensuring the learner can apply the insight as it is being measured.
The Takeaway
The single biggest challenge for companies trying to scale agentic AI training isn't a technological one, it's an andragogical one. The future of agentic AI in education and training is not about having more powerful models or showing off the latest speeds, clever data, or unique applications; it's about embedding deep learning science principles into the very core of the agent. The companies that crack this code won't just be building a better ed-tech product; they'll be building a new standard for human capability.
Mentor126.ai is the only company building agents with an andragogical soul. We are designing tools to help learners progressively apply new skills in appropriately challenged situations. We are collecting the right data to prove that their technology is not just a shiny new object, but a tool that truly empowers individuals and, in doing so, provides a measurable and defensible return on investment.
So what is the takeaway? Role play is just one tool in what should be a precisely designed personal learning journey. It's not about the magic and awe it brings, it is about substance and value. If a company is only offering a role play for learning and development, I would think the prudent questions would be "Is that it? What else is there?" Don't let learning be reduced down to one flashy experience; a flash in the pan to distract you from what it really means to learn.
There are many tools and companies that offer role play experiences, but as long as this is all they have, this is all they will be. Role play is one step in a progressive learning process. It can be done well, but needs done at the right time and for the right learner. The limitations aren't a failure of a specific product; it's a systemic failure of ed-tech to prioritize learning science over technological novelty.
