As companies deepen their artificial intelligence initiatives, the major barrier they face is not the sophistication of AI models but the ability to access, mobilize, and operationalize data effectively. This was a central theme at Pure Accelerate 2026, where industry leaders highlighted a shift from treating data as a static resource to embracing a model that puts data governance and strategy at the core of AI success.
Experts including Christophe Bertrand, principal analyst at theCUBE Research, stressed that data has become the primary asset driving AI outcomes, coining the term “data primacy” to describe this new dynamic. The focus has moved beyond mere data storage toward turning data into an active system that fuels operational decisions and insights. This reframing demands enterprises adopt comprehensive data governance frameworks to ensure data accessibility, security, and compliance as AI efforts scale.
Executives from Everpure Inc. and IDC reinforced that governance is the top hurdle for AI adoption, followed by challenges related to data access across siloed environments. They pointed out that successful AI depends on more than infrastructure upgrades; it requires a fundamental redesign of how organizations handle data. Everpure’s Enterprise Data Cloud Success Blueprint was introduced as a practical framework to help enterprises evaluate their data maturity and drive alignment between technology investments, business processes, and AI objectives.