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.
Scoring Rationale
Provides practical, widely applicable operational guidance, but offers limited novelty and rests on single-source, anecdotal grounding.
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