Scaling AI agents with trustworthy data

The new MIT Technology Review Insights report, in partnership with Google Cloud, reveals how data leaders are building trustworthy, scalable foundations for agentic AI

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While more than two out of every three organizations plan to deploy AI agents widely within two years, a major data bottleneck is holding them back: AI today can only access an average of 45% of enterprise data.

In this global research study, MIT Technology Review Insights analyzes the gaps that many organizations still face in getting their data ready for AI, as well as making sure those AI systems can reliably access the information they need to achieve real-time, trusted action across the enterprise. The report also identifies key areas where organizations are deploying AI agents and finds that companies with AI-ready data systems are achieving the strongest results, offering a clear blueprint for others to follow.

Over half (55%) of executives confirm that their current data systems actively prevent them from scaling agentic AI across their enterprise.
Organizations giving AI agents >70% data access ("Data leaders") achieve stronger results and scale more easily than those with <30% access ("Data laggards").
For data leaders, the trust gap effectively vanishes – 100% report "consistently" or "mostly accurate" AI agent decisions.
The report details the primary initiatives leaders prioritize, including improving all data access and enhancing governance with business context.

Scaling AI agents with trustworthy data report

Hear directly from engineering and technology leaders at Shopify, Deutsche Telekom, and HCA Healthcare on how they’ve modernized their data platforms to support autonomous, real-time AI.

Get the report for a deeper look into the survey findings.