Talking to Your Data: Building Conversational BI Spaces with Databricks Genie
"Getting data to models will not work. You need to get models to the data. If somebody says who is a brickster, ChatGPT does not know because it does not have the context." — Rajesh Ramdas, AVP and TechGM, Field Engineering, DatabricksAt #NasscomFutureForge2026, in this session, "The Great Enterprise AI Reset," Rajesh Ramdas, AVP and TechGM, Field Engineering, Databricks, and Ruchika Panesar, Country Head, India & Chief Information Officer, Functions, NatWest Group, joined Sangeeta Gupta, Senior Vice President and Chief Strategy Officer, nasscom.
The conversation examined why enterprise AI adoption often fails to deliver returns, tracing the gap back to fragmented data, lack of shared context, and a habit of reaching for the most powerful model even when a simpler, cheaper approach would serve the task better. It made the case for centralising data with strong governance, building intelligent orchestration layers that route each task to the right model rather than defaulting to a single frontier model, and treating deterministic outcomes as non-negotiable in regulated environments. Careful use case selection, guided by clear business value rather than novelty, emerged as the starting point for any enterprise serious about scaling AI responsibly.
Resetting enterprise AI for genuine impact, the session made clear, depends less on chasing the newest model and more on getting the data, governance, and orchestration foundations right.
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