Why Most AI Projects Never Make It to Production? | Natalia Koupanou
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Why Most AI Projects Never Make It to Production? | Natalia Koupanou
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AI experimentation is easy. Turning those experiments into something that delivers genuine business value is much harder.
In this episode of The Databricks Diaries, Daniel Thornton speaks with Natalia about the realities of taking AI from experimentation into production.
Natalia has spent around a decade working across data and AI, including building AI capability from scratch in a regulated banking environment. She shares practical lessons on what organisations need to get right before they can start delivering real AI impact.
We discuss:
✔️ Why organisations need to start with the business problem, not the technology
✔️ Building the right platform and environments for AI
✔️ How to prioritise AI use cases
✔️ Why early wins can help build confidence and secure further investment
✔️ The importance of measuring real business impact
✔️ Where organisations are currently seeing value from AI
✔️ What the future of AI and self-service could look like
One of the biggest takeaways: don't ask what you can do with AI. Start by asking what problem is worth solving.
Connect with Daniel on LinkedIn:
https://www.linkedin.com/in/databricksdan/
Learn more about Primus Connect:
https://www.primus-connect.com/
#Databricks #AI #ArtificialIntelligence #DataEngineering #DataLeadership