Why AI Agents Are Forcing Enterprises To Rebuild Their Data Foundations

What happened

Making it usable for AI is proving harder. Systems built for different teams, functions, and use cases have left information scattered across databases, applications, and workflows.

For AI systems expected to reason across an organisation, having data somewhere is not enough. The gap is becoming visible as Indian businesses move AI from pilots to production.

According to a Dun & Bradstreet survey , 73% of surveyed Indian businesses report some measurable returns from AI investments, but only 4% say their enterprise data is fully ready to support AI at scale. Closing this readiness gap means addressing years of accumulated data debt.