The Three Employee Types Blocking Your AI Rollout - Dr. Gleb Tsipursky

AI adoption in the workplace is failing at an alarming rate—95% of AI pilots never scale, according to an MIT study. The problem isn’t the technology; it’s the psychology behind how employees and leaders respond to AI. In this episode, behavioral scientist Dr. Gleb Tsipursky reveals why most companies get AI adoption wrong and how to fix it.

Dr. Tsipursky, author of The Psychology of AI Adoption at Work: From Resistance to Results, breaks down the three types of resistance holding back AI adoption:

AI Alarmists (fear of job loss)Pragmatic Resistors (identity threats to professional roles)Reluctant Adopters (shame and stigma around AI use)

You’ll learn why traditional change management strategies don’t work for AI and what leaders can do to overcome these barriers. From focusing on growth (not job cuts) to turning "shadow AI" users into AI champions, this episode provides the evidence-based playbook for scaling AI successfully.

Why the Topic Matters

AI isn’t just another tool—it’s a fundamental shift in how work gets done. Companies that fail to adopt AI effectively risk losing market share, productivity, and talent. Meanwhile, those that get it right grow revenue 9% faster and headcount 6.5% faster (Stanford research). This episode is a must-listen for executives, HR professionals, and anyone navigating the future of work.

Key Takeaways

The three psychological barriers to AI adoption and how to address them.Why focusing on growth (not job cuts) reduces fear and resistance.How to turn "shadow AI" users into AI champions.The role of leadership modeling, gamification, and psychological safety in AI adoption.Actionable strategies for mid-size companies (50–5,000 employees).

Who Should Listen

Executives and leaders responsible for AI adoption.HR and change management professionals.Consultants and advisors helping companies implement AI.Employees navigating AI resistance in their organizations.Anyone interested in the future of work and behavioral science.

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