In sales education, practice matters.
Students can study case materials and prepare for presentations in class, but real progress in sales often comes when they have to respond in the moment — asking questions and fielding objections in real time.
That kind of training is valuable, but it is also difficult to scale.
For Michael Johnston, a well-respected sales professional who now teaches in Gatton’s sales program, that challenge became the starting point for a new classroom approach: using artificial intelligence to expand opportunities for students to practice and receive individualized feedback outside the classroom.
“At the core, the challenge is scaling high-touch, interactive sales training across hundreds of students,” Johnston wrote in materials describing the project. With faculty-to-student ratios often reaching 45 to 1 or higher, he noted that it is difficult for instructors to provide the one-on-one coaching needed to prepare every student for real-world sales conversations.
Rather than replacing faculty instruction, Johnston’s process is designed to extend it.
He begins by identifying a specific learning objective, such as helping students improve an elevator pitch, conduct a discovery call or respond to customer objections. From there, he uses Google’s Gemini to generate the content behind a sales scenario, including company background, customer needs and business context. That scenario is then built into Yoodli, an AI-powered communication platform that allows students to engage in interactive verbal role-play. He also uses Vyond to create customized training videos that make case material more engaging for students.
The result is a process that gives students access to realistic, replicable practice on their own schedule, while also giving instructors more time to focus on higher-level coaching.
According to Johnston, tasks that once took four to eight hours to build manually can now be completed in under an hour, and role-play practice that once depended on limited instructor time can now be made available to entire classes simultaneously.
In the AI role-play environment, students work through scenarios that mirror professional sales situations. Johnston can define the customer persona, set the evaluation criteria and build in specific objection triggers or decision points. Students then conduct verbal conversations with the platform and receive immediate feedback on their performance.
That feedback can include scores, attempt history, speaking time, video recordings and call analysis. Johnston then reviews the results and incorporates them into the broader course structure.
The approach addresses a practical problem in business education: students need repetition, but not all repetition needs to happen live in class.
By moving early-stage practice into an AI-supported setting, Johnston gives students a lower-stakes way to build confidence before stepping into peer role-plays, interviews or employer-facing conversations.
The project also reflects a broader shift in how business schools are thinking about AI.
In Johnston’s model, the technology is not the lesson itself. It is a tool to help deliver more practice, more consistency and more accessibility.
Students benefit from 24/7 access to practice environments and private, individualized coaching. Faculty benefit from fewer repetitive drills and more time for deeper teaching. And as enrollment grows, the sales program can maintain a consistent training experience across a larger number of students.
Johnston also emphasizes that the process is adaptable beyond sales. The same workflow could be used across the Gatton College for mock interviews, client presentations or difficult workplace conversations, making it a flexible model for professional skill development in multiple disciplines.
Johnston notes several lessons learned so far: students are creative, the role-play platform is flexible and scalable, and AI-generated case studies make it easier to customize practice to fit course goals. At the same time, he makes clear that the technology works best when paired with faculty guidance and coaching.
That balance may be what makes the approach especially useful in an education setting.
Rather than treating AI as a flashy add-on, Johnston is using it to solve a real classroom problem: how to help more students practice the adaptability that modern sales roles require.
For Gatton, the result is a teaching model that is both current and practical that reflects the college’s interest in emerging technology while staying focused on what matters most: preparing students to perform in the real world.
