WILMINGTON, DE — EnterpriseDB (EDB) released new global research showing that most enterprises are struggling to scale agentic and generative AI, with 87% at risk of falling behind due to siloed data, fragmented infrastructure, and underused AI capabilities.
The study, Sovereignty Matters: A Global Blueprint for Sovereign, Agentic, and Generative AI, surveyed 2,050 senior executives across 13 countries and analyzed more than 15,000 simulations and 500 variables. It found that companies making AI and data sovereignty mission-critical are seeing returns up to five times higher in innovation, efficiency, and long-term competitive value.
These leading organizations, dubbed the “Deeply Committed,” account for just 13% of enterprises surveyed. They have built platforms that secure, govern, and integrate data across hybrid environments, enabling them to deploy twice as much mainstream agentic and generative AI as their peers.
“The enterprises seeing real returns from agentic and GenAI have something in common: They’ve made sovereignty over their AI and data a deliberate foundation of their platform strategy, not an afterthought,” said Kevin Dallas, CEO of EDB.
The report contrasts the Deeply Committed with the “Strivers,” “Half-Ins,” and “Sideliners” — organizations that are experimenting with AI but lack the infrastructure and governance needed to scale. While 95% of enterprises aspire to run their own AI and data platforms by 2028, most remain stalled in early stages.
IDC research director Devin Pratt emphasized that “success hinges on AI and data that is sovereign by design—available anywhere, in any form you need.” Hybrid environments and open technologies like Postgres, the report noted, provide a foundation for scaling AI securely and effectively.
Among the findings: the Deeply Committed achieve 5x ROI, are 2.5x more confident in evolving into industry leaders, and are significantly outpacing competitors in AI deployments.
The report includes global benchmarks, industry-specific insights, and a self-assessment tool to help organizations gauge their readiness. It also underscores the importance of hybrid architectures and open platforms in building sovereign AI systems capable of meeting enterprise and regulatory demands.
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