AI, Generative AI, Business Strategy, Analytics, Emerging Technology

In this thought-provoking session from the Artificial Unintelligence Conference, Dan Banas, AI Strategy and Analytics Consultant, explores why so many AI projects fail — and what separates those that succeed.

Drawing on more than 15 years of experience advising Fortune 500 companies, Dan breaks down the hidden pitfalls behind failed implementations: unclear objectives, over-engineering, and a lack of alignment between business goals and technology. His message is clear — the problem isn’t AI itself, it’s how we approach it.

Key ideas explored:
• Why most AI failures are strategic, not technical
• How to shift from “Can we build it?” to “Why should we?”
• The danger of over-engineering before proving value
• The “airport analogy” — designing AI as a system, not a silo
• How to move from one-off AI projects to lasting organizational habits

Dan’s talk reframes AI success as a matter of perspective and discipline, offering practical insights for executives, data leaders, and practitioners alike who want to make AI work — not just make it interesting.