Case Study 2: AI Adoption Research and Facilitation with ebbf (Ethical Business Building the Future)

Practitioner Research · AI Adoption · Facilitation · Cross-Industry Insight

Context

ebbf is an international network of professionals and business leaders focused on ethical business practice. As AI moves from experimentation into everyday work, its members were asking the same questions organizations everywhere are asking: what is actually happening beyond the ‘AI Hype”, where do organizations get stuck, and what does effective adoption require.

I proposed and now lead a four-part virtual series on AI adoption. The series is deliberately structured as practitioner reflection rather than training. Participants are not being taught how to use AI. They are being guided to examine their own use of it, the obstacles they are running into, and what would need to change for adoption to work in their organizations.

What I Am Doing

I design the framing and reflection questions for each session and facilitate participants through them in breakout groups with plenary report-back. The questions are built to surface specifics: which use cases are actually in play, where adoption has stalled, and what would have to change for the next step to be possible.

The series also extends the market research I am conducting independently with senior leaders across industries on organizational AI adoption. Both streams serve the same objective, which is building an accurate, current picture of where AI adoption is breaking down in practice rather than in theory. Responses are kept anonymized and aggregated.

This work directly informs my advisory practice. The patterns emerging across sectors and geographies shape how I diagnose adoption problems and design programs for clients.

Outcome

Engagement in progress. Case study will be updated as the series develops.

Session one took place in September 2026 with over 30 participants from more than 20 countries. A consistent theme emerged early: practitioners are overwhelmed by the volume of AI use cases available to them and far less clear on what actually needs to change inside their organizations for adoption to hold.