The Top Reasons for AI Project Failure – and What you can Do about it
September 20 @ 11:30 AM - 1:00 PM
Artificial intelligence and advanced data projects are gaining rapid traction. However, with all this interest and hype in AI, only a small percentage of AI projects are actually seeing success. Why are so many AI projects failing when they don’t need to? With all the resources, great technology, and skilled talent put towards building AI projects, we shouldn’t be seeing so much AI project failure, but up to 80% of AI projects are not being completed successfully or achieving critical success measures. Clearly it’s not a technology or people problem, so what could be the main issues holding back AI project success?
Leveraging experience with thousands of AI projects and experience through best-practices approaches to AI, Cognilytica shares in this webinar the most common reasons for AI project failures and the insights to be learned from those failures. In this webinar we will discuss common reasons we see AI projects fail, the risk of overpromising and underdelivering on AI capabilities, methodologies and processes that can guarantee a higher rate of success, and how to avoid the common traps and pitfalls that usually beset AI projects.Register Here