Your AI Is Only as Good as Your Data: Unlock the full potential and scale of enterprise AI

Only 15% of organizations in India have scaled AI today — 85% remain locked in pilots. And the most telling reason isn't lack of ambition. It's the state of enterprise data — not the sophistication of the models — that is emerging as the real determinant of who can scale.

Data is scattered across clouds, on-prem systems, SaaS platforms, and document repositories. It's duplicated, ungoverned, and too slow to be useful in real time. When an AI system produces an output that's wrong or can't be explained to a regulator, the root cause almost always traces back here.

The leaders pulling ahead aren't doing so because they use more AI — they're reshaping the data foundations AI needs. The question for this session is: what does that actually look like in practice?

We'll work through five problems that are quietly keeping Indian enterprises stuck in pilot mode — and how leading teams are solving them:

• "Our data is everywhere and trusted nowhere" — 68% of Indian executives cite complexity of interconnecting data sources and 57% cite inconsistent data quality as their biggest data fabric challenges. What it takes to connect distributed data across clouds, on-prem, and SaaS — without moving it, duplicating it, or rebuilding your architecture.
• "We're paying for data infrastructure that can't keep up with AI workloads" — How a multi-engine lakehouse architecture lets you match the right query engine to the right workload — so analytics, AI, and BI stop competing for overprovisioned, overpriced compute.
• 90% of our data is locked in documents, contracts, and files that AI can't reach — How modern platforms ingest, enrich, and make unstructured enterprise data queryable — not just stored — so your AI actually knows what your business knows.
• "We can't explain or defend what our AI outputs" — What built-in governance, lineage, and access controls look like when they're embedded in the data layer itself — so every AI answer is traceable from source to decision.
• "We've been in AI pilot mode for 18 months and can't get to production" — The next wave of AI scale in India will depend on platforms that can move data from where it is created to where it is needed, instantly and securely, across applications, APIs, and clouds. What the data infrastructure decisions actually look like for organizations that have crossed that line.