You Need To Stop Doing This On Your AI Projects

Brandon McGee

4 years ago

“One of the biggest reasons for AI project failure is that companies don’t justify the use of AI from an return on investment (ROI) perspective. Simply put, they’re not worth the time and expense given the cost, complexity, and difficulty of implementing the AI systems.
Management guru Peter Drucker once famously said, ‘you can’t manage what you don’t measure.’
Another big reason why companies aren’t seeing the ROI they are expecting is that projects are trying to bite off way too much all at once…best practice AI methodologies such as CPMAI clearly advise project owners to ‘Think Big. Start Small. Iterate Often.’
Organizations are now seeing benefit in employing approaches such as the Cognitive Project Management for AI (CPMAI) methodology, built upon decades-old data centric project approaches such as CRISP-DM and incorporating established best-practice agile approaches to provide for short, iterative sprints for projects.”