A joint IDC and Lenovo study reports that 88% of AI proof-of-concept (POC) projects fail to reach production because of unclear objectives, unprepared data, and a lack of in-house agentic AI expertise. These result in a build-vs.-run split, where the team that designed and deployed AI agents, often an agentic AI partner, doesn’t get to run them over the business processes. When the operating team, often experienced on demo, uses the agentic system without any external help, errors arise. Operational gaps can cause cascading failures and business catastrophes if a single agent deviates from...

Source: The New Stack