Enterprises often start their AI journey by choosing a model, yet failed projects usually trace back to unprepared data, poorly chosen scenarios, and unclear accountability. Before deployment, ask three questions: Is the data ready and compliant to feed the model? Is the scenario frequent, measurable, and low-risk? Who reviews AI output and owns the outcome? Getting these foundations right matters more than picking the newest model. This article is compiled from publicly available industry information.
Enterprise AI