Data Readiness: Why 52% of AI Fails

AI is only as good as the data behind it. In our new episode, I sat down with Makesh Renganathan from Informatica’s product team to talk about what it really takes to get data AI-ready and ship use cases that move the needle.

Highlights:

* Only 48% of AI projects make it to production. The gap is data readiness.

* Start with clear outcomes. Then build the foundation: completeness, quality, context, governance, security, and timely delivery.

* Biggest blockers today: fragmented sources across legacy and cloud, 80–90% untapped unstructured data, and missing guardrails for trust and lineage.

* Quantity is not quality. Clean and diverse data beats “more data.”

How Informatica helps:

* One platform with IDMC to connect, transform, and integrate at scale, including RAG ingestion.

* Deep metadata and lineage to add context and trace outputs back to sources.

* Built-in governance and data quality to keep sensitive data controlled and compliant.

* Low-code and AI-assisted build with CLAIRE so existing teams can deliver faster, from pipelines to agents.

Rapid takeaways from Makesh:

* Treat data as a strategic asset before you scale models.

* The future is AI-driven data management that automates integration, quality, and governance so people focus on strategy.

The episode is live now. Watch and tell me which part resonated with your current AI stack.

#data #ai #informatica #theravitshow