Jun 8, 2026
Get the free Core Drives in the Wild guide, behavioral design applied to real corporate cases: professorgame.com/WildCD
Episode Summary
Rob breaks down why enterprise AI adoption stalls even with paid licenses and training, while a group of students beat a locked, proctored exam with ChatGPT and no support at all. Reading both cases through the Octalysis Framework, he shows how the exam accidentally stacked Core Drive 8 (Loss & Avoidance), Core Drive 6 (Scarcity & Impatience), and Core Drive 2 (Development & Accomplishment) into a ferocious, if mispointed, motivation engine. The enterprise bought the most capable tool and surrounded it with zero motivation, so nobody opened the app. Listeners learn why AI adoption is a motivation problem wearing a tooling costume, and leave with a two-part diagnostic question to ask of any AI initiative.
About the Host
Rob Alvarez is Head of Engagement Strategy, Europe at The Octalysis Group (TOG), a leading gamification and behavioral design consultancy. A globally recognized gamification strategist and TEDx speaker, he founded and hosts Professor Game, the #1 gamification podcast, and has interviewed hundreds of global experts. He designs evidence-based engagement systems that drive motivation, loyalty, and results, and teaches LEGO® SERIOUS PLAY® and gamification at top institutions including IE Business School, EFMD, and EBS University across Europe, the Americas, and Asia.
Key Takeaways
- Students beat a lockdown, proctored, face-to-face online exam by getting ChatGPT to answer questions live through a Chrome extension, with no license, no training, and no change management. Adoption was instant, total, and creative enough to defeat the security.
- The exam accidentally stacked three Black Hat Core Drives: Core Drive 8 (Loss & Avoidance, failing is high-stakes), Core Drive 6 (Scarcity & Impatience, one timed shot), and Core Drive 2 (Development & Accomplishment, clearing the hurdle to the grade).
- Enterprises buy the paid license, training, IT support, and a leadership mandate, then adoption stalls because none of those things are motivation. There is no personal loss for ignoring the tool and no personal win for using it.
- Motivation pointed at the wrong goal produces flawless adoption of exactly the behavior you did not want. The students aimed AI at passing, not learning, and got it.
- As AI removes capability constraints, the human motivation layer becomes the only constraint left, which is why behavioral design matters more in the AI era, not less.
- The diagnostic: ask what your team personally gains by using the tool and what they personally lose by ignoring it. If the honest answer is "nothing much either way," no rollout plan will save it.
Topics Covered
- 0:00 - Students hacked a locked exam
- 0:52 - Same tech, opposite outcome
- 1:44 - Adoption was never the problem
- 2:39 - The exam's accidental motivation engine
- 4:31 - Almost entirely Black Hat motivation
- 5:18 - Why the funded enterprise stalls
- 6:30 - Adoption and direction both matter
- 7:41 - Why behavioral design matters with AI
- 7:55 - Your diagnostic question for today
Mentioned in This Episode
- The Octalysis Framework, developed by Yu-kai Chou
- ChatGPT (OpenAI)
- Core Drives in the Wild, the Professor Game free guide