EDM Association released its 2026 Global Data Management Benchmark Report, revealing that many organizations are rapidly increasing investment in artificial intelligence without first establishing the necessary data, governance, and operational foundations for success. Based on input from more than 435 organizations across 50+ countries and grounded in the EDM Association’s Data Management Capability Assessment Model (DCAM®), the study highlights a clear gap between AI ambitions and enterprise data readiness.
The 2026 Global Data Management Benchmark report findings point to a trend behind why many AI initiatives fail: organizations are approaching AI from the wrong starting point. Rather than building strong data foundations, governance frameworks, and clear business cases, enterprises are prioritizing AI tools and use cases first, limiting their ability to scale and deliver measurable results.
“AI is becoming a stress test for enterprise data,” said John Bottega, President of EDM Association. “Many organizations are moving aggressively into AI, but without the consistent, operational data foundations required to support it. Putting technology ahead of trusted data and governance explains why so many initiatives struggle to deliver better results.”
Key Findings from the 2026 Benchmark
The report highlights several structural gaps that are directly impacting AI success:
- AI investment is outpacing data readiness: Approximately 31% of organizations surveyed report advanced data strategy capability, leaving most without the foundation required to support AI at scale
- Analytics programs are widespread, but not operational: While 77% of organizations surveyed have established analytics capabilities, only 19% demonstrate mature adoption and education, revealing a significant gap between investment and execution
- The Chief Data Officer role is now mainstream, but still evolving: More than 70% of organizations have appointed a CDO, yet high turnover and unclear authority structures continue to limit the role’s impact
- Governance is improving, but not keeping pace with AI demands: While over 70% report formal governance structures, many lack the funding models, measurement frameworks, and enterprise alignment required to operationalize them
- Workforce readiness is a critical constraint: Weakness in data literacy, analytics education, and organizational adoption are limiting the ability to scale both data initiatives and AI programs
“The organizations that succeed with AI will be the ones that treat data management as a business capability, not just a technical prerequisite,” Bottega added. “This year’s benchmark shows that progress is real, but requires a commitment to governance, data quality, and the ability to execute consistently across the enterprise.”
In addition to the report, EDM Association introduced a new Benchmark Repository and Dashboard, developed in collaboration with EDM Association Authorized Partner, Element22 and their Pellustro benchmark technology. This platform enables member organizations to compare their data management capabilities against the benchmark and global peers and track progress over time. This will build an anonymized repository of benchmark data for increasingly more robust analysis. As the Benchmark study is aligned to DCAM, the report itself provides additional context for performing and analyzing assessments using the DCAM framework, helping organizations identify gaps, prioritize improvements, and build the data and governance foundations required to support AI.
The 2026 Global Data Management Benchmark Report is available for download at the website here.
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