Date -2026-05-14 Location - WILMINGTON, Del.
AI and data sovereignty have become the single strongest predictor of enterprise AI success, according to a new MIT Technology Review Insights report produced in partnership with EnterpriseDB (EDB). The research explains how organizations “Deeply Committed” to controlling their data, infrastructure, models, and governance are delivering 5x the ROI on generative and agentic AI initiatives—at a moment when more than half of enterprises already have autonomous agents in production making real-time decisions on operational data.
The report, Establishing AI and Data Sovereignty in the Age of Autonomous Systems, draws on an EDB global survey of more than 2,000 senior executives across 13 countries, combined with more than 15,000 simulations across 500+ variables and interviews with leading experts in AI, cybersecurity, data governance, and enterprise infrastructure. Modeled analysis shows a 0.93 correlation between sovereignty commitment and AI success outcomes — the strongest single driver identified in the study.
Key findings:
“As enterprises continue evaluating AI adoption strategies, the report explores how sovereignty may involve a shift from simply consuming AI services toward developing a clearer understanding of the architecture and systems that govern them,” says Laurel Ruma, global director of custom content at MIT Technology Review Insights. “It also reflects how many organizations may be reassessing questions of control and long-term AI strategy as autonomous systems continue to evolve.”
The findings arrive as enterprises enter the agentic era, in which AI systems no longer just generate outputs but take actions and trigger workflows around the clock, with minimal to no human oversight. With more than 1 billion active agents projected by 2029 executing 217 billion actions per day, the report shows that AI and data sovereignty are becoming the operational foundation of how agents reason, decide, and act.
“Sovereignty defines which agents can touch the data, in which region, under which policies, and how all of that is monitored and audited,” said Devin Pratt, research director at IDC, in the report. “Rather than being a brake on agentic AI, sovereignty sets the safe operating boundaries that allow organizations to scale with confidence.” Pratt also draws a clean line between the two concepts: “Sovereign data governs the information; sovereign AI governs the systems that act on that information.”
That governing role is precisely why the report frames sovereignty as the operating system for agentic AI, not a policy layer on top of it. In the report, Mukesh Chandak, director of Strategy and Innovation, Cloud & AI at Thales, argues that sovereignty is what unlocks the highest-value AI use cases rather than constraining them.
The economic stakes are unambiguous in the data. Kevin Dallas, CEO of EDB, frames the strategic question driving the shift: “Data is really a new currency; it’s the IP for many companies. The big concern is, if you’re deploying an AI-infused application with a cloud-based large language model, are you losing your IP? Are you losing your competitive position?”
In the report, Michael Schrage, research fellow at the MIT Sloan School’s Initiative on the Digital Economy, unpacks why governance frameworks built for static data estates aren’t enough for systems that act autonomously. He warns that sovereignty cannot be a one-time exercise in an environment in which models, agents, and multi-agent workflows evolve weekly.
The report also surfaces a leadership gap that’s slowing response time. “The C-suite is quite behind in terms of understanding AI in general, let alone the nuances of data sovereignty and ownership and policy and driving those policy guidelines,” said Faisal Hoque, founder of SHADOKA and NextChapter, in the report. “Sovereignty is not isolation. It comes from having discipline of control, evidence, and choices.”
Beyond the survey findings, the report examines emerging technologies and operational models enabling sovereign AI at enterprise scale, including confidential computing, edge AI, post-quantum cryptography, converged data platforms, and open source infrastructure such as PostgreSQL. It also provides enterprise leaders with a practical “90-day sovereignty sprint” framework for mapping sensitive data, establishing governance guardrails, creating secure environments for AI experimentation, and deploying sovereign AI initiatives in phased, real-world use cases.
“We’re in an AI-first, sovereign-first world. Build your own sovereign data and AI factories. Lead from the front. Disrupt or be disrupted,” said Dallas.
Download the full report here: https://www.enterprisedb.com/resources/MIT-Technology-Review-Report
About EDB
EDB Postgres® AI (EDB PG AI) is the first open, enterprise-grade sovereign data and AI platform—secure, compliant, and scalable, on-premises and across clouds. Built on Postgres, the world’s leading database, EDB PG AI unifies transactional, analytical, and AI workloads, enabling organizations to operationalize their data and LLMs while maintaining control over sovereign environments. EDB PG AI is supported by a global partner network and delivers up to 99.999% availability as well as hybrid management and a built-in AI factory. As one of the most active contributors to the PostgreSQL project, EDB is deeply invested in the vitality of the global community. To learn more, visit www.enterprisedb.com.
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Anwar Ahmad
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(347) 206-5651
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