Why most enterprise AI pilots never make it to production — And what fixes that
Every CIO has a version of the same slide by now: dozens, sometimes hundreds, of AI pilots scattered across the business, each one promising. Few of them ever become systems the enterprise actually depends on. According to Bharat Chadha, Partner, Tech Consulting at Uniqus Consultech, that gap has a specific, identifiable cause — and it isn’t the AI model.
“The single biggest bottleneck is the data and context layer, and not the model,” Chadha says. Pilots tend to succeed because they run on curated, hand-picked datasets built to make the demo work. Production is a different animal entirely: the system now has to reach across ERP, CRM, documents and workflows in real time, while respecting permissions, business rules and regulatory constraints. The instant users can’t trust the source, quality or security of the data behind an answer, they quietly stop trusting the output — regardless of how capable the underlying...
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