ai-strategy

Coverage of how organizations decide where AI fits, sequence their investments, and close the gap between prototypes and production systems that move real metrics. Expect practical thinking on prioritization, build-versus-buy choices, data and workflow readiness, organizational change, and defining success before writing code. The focus stays on the decisions and trade-offs that separate AI initiatives delivering durable value from those that stall after the demo.

ai-adoption, enterprise-ai, ai-implementation, change-management, ai-strategy

The Last Mile Problem of AI: Why Building the Demo Is Easy and Delivering Value Is Hard

Building an impressive AI demo has never been easier, but most organizations fail to turn prototypes into production systems that deliver real business value. The true barriers are data fragmentation, workflow integration, organizational change, and undefined success metrics, not model quality.