The Trust Erosion Cycle: What AI Failures Are Actually Telling Us
About this session
As an industry, we are finding out in real time what it actually means to run AI in production.
The numbers are not encouraging. 95% of generative AI pilots produce no measurable financial return. 42% of companies abandoned most of their AI initiatives in 2025 alone. And the diagnosis is consistent across every study: the failures are not about model quality, API access, or compute budgets. The technology works. The organizations around it often do not.
The reason is simpler than most people want to admit. We are leading probabilistic systems with deterministic instincts. We set expectations like the output will always be consistent. We assign accountability like failure has a clear owner. The biggest AI failures are not technical. They are organizational: weak controls, unclear ownership, and misplaced trust.
That pattern has a shape. I call it the Trust Erosion Cycle. Overcommit, normalize, incident, scramble, reset or repeat. Your team has probably lived some version of it already.
The exit from that cycle is not a better model. It is better agreements, made earlier, with the right people, about what the system can and cannot promise. In this session I will walk you through two frameworks I have developed from years of leading engineering organizations through exactly this problem. The first is the Trust Erosion Cycle, so you can recognize exactly where your organization is sitting right now. The second is the Uncertainty Operating Agreement, so you know what to do about it before the next incident, not after.
You will leave with both frameworks and a clearer picture of what responsible AI leadership actually looks like when the stakes are real.
Speaker
Key takeaways
- How to recognize the organizational failure patterns that show up when AI moves from pilot to production, and diagnose exactly where your organization sits in the Trust Erosion Cycle
- Why the management instincts that work for deterministic systems break down when AI is in the critical path, and what to do differently as a leader
- How to apply the Uncertainty Operating Agreement to align engineering, product, legal, security, and business stakeholders before deploying AI, not after something goes wrong