Organizations Adopt Frameworks To Scale AI Products

This article analyzes why roughly 80% of AI projects and nearly 90% of PoCs fail to reach production, attributing failures to poor product-market fit, weak data infrastructure, and organizational resistance. It outlines core evaluation areas—value proposition, people, processes, technology—and recommends an eight-step PoC/MVP framework to improve operationalisation, scalability, and ROI. Practitioners are urged to validate feasibility, define KPIs, and align solutions with enterprise architecture before funding pilots.