Why Enterprise AI Initiatives Keep Dying Before Production

Most enterprise AI projects never reach production — and the models aren’t to blame. In a recent InformationWeek column, Brillio CTO Chander Damodaran breaks down the three systemic patterns that kill AI initiatives before they deliver value: data quality gaps that go unexamined, fragmented ownership across siloed teams, and governance that gets deferred until it’s too late.

Drawing on research showing 95% of pilot failures trace back to data and integration problems, Damodaran challenges executives to ask harder questions before greenlighting projects — about data lineage, production readiness, and cross-functional accountability. His message is direct: approving a demo is not the same as approving a deployment.

For technology and business leaders navigating AI investment decisions, this is essential reading.