The enterprises seeing the most success are what Google and MIT refer to as “data leaders,” those that give AI systems access to more than 70% of their data. “Data laggards,” by contrast, share just 30% or less of their data with AI. Interestingly, 100% of data leaders say their agents make “mostly” or “consistently” accurate and relevant decisions, while just 22% of data laggards say they have that trust.

Agents need what the report calls “frictionless access” to operating systems, multimodal data, and context, helping them understand how data maps to different teams’ goals. “The most important initiative to enable scaling among all respondents is improving access to structured and unstructured data for AI agents.”

To successfully scale agents, the report recommended that enterprise leaders prioritize several data initiatives. First, improve access to data; discover, inventory, and classify data, both structured and “dark”/unstructured. After governance principles are applied, information can then be extracted and connected to AI agents.