Data context and governance are the missing ingredients keeping enterprise AI from scaling
The next phase of enterprise AI is shifting focus from models to the data that fuels them, with organizations increasingly investing in AI-ready data foundations. As regulatory requirements grow and data environments become more complex, companies are prioritizing data intelligence strategies that provide the visibility, context and governance needed to scale AI responsibly.
AI is transforming how work gets done, with intelligent agents increasingly able to make decisions and carry out tasks independently. To unlock that potential, organizations must understand their business processes and apply the right intelligence and context, enabling faster execution while freeing up resources for innovation, according to Ashish Gupta (pictured), chief executive officer, president and chairman and board member of 1touch.io Inc.
“I feel AI is going to be very, very productive for everyone in the market,” Gupta said. “But it’s going to be very productive only if you’ve got the right data context driving that accuracy.”
Gupta spoke with theCUBE’s Christophe Bertrand and co-host Alison Kosik at the Pure Accelerate 2026 event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the growing importance of data context for AI accuracy and the role of governance in building AI-ready data foundations. (* Disclosure below.)
