How Boards Can Shape AI Strategy

Many promising Generative AI initiatives fail to move beyond the pilot stage due to a lack of enterprise readiness for operationalization. Common hurdles include poor data quality, inadequate security protocols, escalating costs, and a lack of clear business value or MLOps maturity. To succeed, organizations must build comprehensive systems that feature customized models, low latency, robust security, and mature MLOps capabilities. Key strategies for scaling involve domain-specific customization, implementing human-in-the-loop oversight, and designing flexible, modular architectures.