2026 Report Uncovers What's Holding Back Enterprise AI and Decision-Making

The Modern Data Report 2026:The Data Activation Gap, conducted by the Modern Data 101, a community and publication for anyone who works with data, from team leaders to platform builders to analysts. The survey gathered insights from more than 540 data practitioners across industries and around the globe between October 2025 and January 2026.

The report examines why turning enterprise data into everyday business decisions and AI at scale remains a challenge, even as organizations invest heavily in data platforms and expand AI initiatives.The findings show that the challenge is not a lack of tools or ambition, but activation: ensuring data is discoverable, contextual, and trustworthy at the moment it's needed for decisions and AI workflows. Without these foundations, enterprises generate insights but struggle to translate them into consistent action or measurable impact.

Key findings include:

• 84% say they encounter conflicting versions of the same metric, with more than one-third experiencing this regularly.
• 68% say their data is not clean or reliable enough for AI use cases.
• 46% report they do not fully trust the data used for business decisions.
• 89% rank finding the right data among their top three most time-consuming tasks, while 62% say actual analysis takes the least amount of their time.

"Across the industry, it's clear that many AI initiatives are struggling to move beyond experimentation," said Saurabh Gupta, President and CEO of The Modern Data Company. "This research helps explain what's holding them back. What we're seeing isn't a problem with AI algorithms, it's a data activation problem, especially lack of context. Enterprises have invested heavily in data platforms and AI tools, but too often the data feeding those systems can't be accessed, understood, or trusted when real decisions need to be made. AI doesn't solve that gap, it exposes it. Closing the activation gap by ensuring data has full context is what turns pilots into production."

Where practitioners say progress should begin

Eighty percent of respondents identify a unified semantic layer with standardized definitions as the single most important enabler of AI value, ranking it ahead of better AI models, additional tools, or more advanced features. Without a shared understanding of what business metrics mean, neither people nor AI systems can act on data consistently.

When these foundations are in place, the business impact is clear

Eighty-seven percent of respondents say faster, more reliable access to high-quality data improves decision-making speed, 78% report increased confidence in decisions, and 66% point to improved business KPIs. Together, the findings position semantic alignment and core data foundations not as technical nice-to-haves, but as strategic drivers of business performance.

The full report explores these themes in depth across business impact, AI readiness, day-to-day data realities, discovery challenges, collaboration dynamics, platform limitations, and the growing demand for converged data foundations.

Download the report here.