Successful AI implementation requires treating systems as a living asset that requires continuous monitoring and governance. Too often, IT leaders overlook important qualities such as risk assessment, data quality management and contingency strategies during the planning stages, unveiling hidden costs down the road.
In this interview, technologist and educator Daryle Serrant discusses the often-overlooked risks and potential financial fallout associated with implementing artificial intelligence in business environments. Serrant points to real-world examples where well-meaning AI project managers underestimated the time required to maintain high-quality data sets, prepare for regulatory requirements, or run AI complex business solutions. He also provides advice on how to avoid these costly mistakes by continuously monitoring AI technology post-implementation.
