Lessons Learned from AI Project Failures

Far too often, organizations are running data and AI projects without following established best practices and taking the right steps to ensure their success. Decades ago, we learned how to run application development projects using best-practice agile and iterative approaches. However, many organizations are failing to apply similar best practices to their data-centric projects. Without a proper approach that standardizes steps for data preparation, data identification, and data protection, it’s hard to achieve the success you’re expecting.

In this presentation we’ll walk through a data and AI best-practice methodology to provide you with the foundation needed for project success, especially as you incorporate advanced analytics and AI projects. The CPMAI methodology is the industry’s best practice for AI & ML projects.