Why AI Projects Fail and How to Get Them Right
AI has never been more accessible. In just the past few years, organizations have gone from experimenting with machine learning to rapidly building applications powered by large language models and generative AI.
It’s now possible to create something that looks like a fully functional AI solution in a matter of days.
But that speed is also part of the problem.
More companies are starting AI projects than ever before, yet more of those projects are failing to deliver real impact.
In a recent webinar, Dr. Tim Oates breaks down why this is happening. Drawing on years of experience in AI consulting, he explains where organizations go wrong and what it actually takes to build AI systems that work in production and drive measurable business value.