India, Dec. 29 -- Vice President, Field Engineering, Asia Pacific and Japan, Databricks

AI has reached a point where it can meaningfully accelerate enterprise productivity. The central challenge for organisations is no longer gaining access to more powerful models, but refining and deploying AI in ways that reliably automate routine, time-consuming work. Done well, this frees teams to focus on higher-value, creative and strategic tasks.

Closing the gap between AI's potential and its reliability will define 2026. Rather than chasing ever-larger models, enterprises are beginning to demand smarter, contextual systems that align closely with their specific needs. Six shifts are emerging as critical: building agents that reason over propriet...