Why Most AI Projects Never Make It to Production | Natalia Koupanou & Daniel Thornton

AI is moving incredibly quickly, but turning an AI idea into something that delivers real business value is a very different challenge. In this episode of The Databricks Diaries, Daniel Thornton speaks with Natalia about what it actually takes to move AI from experimentation into production. They discuss: ✔️ Why many AI projects struggle to get beyond the POC stage ✔️ The importance of starting with the business problem, not the technology ✔️ Building the right platform, governance and risk appetite ✔️ How organisations should prioritise AI use cases ✔️ Why early wins can help build confidence and unlock further investment ✔️ What happens when an AI project fails ✔️ Where organisations are seeing real value from AI today ✔️ Why AI could eventually become as self-serve as BI ✔️ What the next few years could look like for AI Natalia also shares lessons from building AI capabilities in regulated environments and explains why businesses need to become comfortable with constant change. Hosted by Daniel Thornton 🎧 Listen to the full episode on Spotify: