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InnovationResearch

Benchmarks

EDM Association Research

In support of our membership, the EDM Association conducts research into a variety of data management topics and evolving trends. Such topics include defining data management capability and benchmarks; advanced analytics, AI and machine learning; cloud data management; and evaluation of regulations – and their data management impacts.

Global Industry Benchmarks

As part of the agenda for data management research, the EDM Association conducts periodic benchmark studies, using DCAM® (Data Management Capability Assessment Model) or CDMC (Cloud Data Management Capabilities) as the framework for the analysis.

NEW! 2026 Global Data Management Benchmark Report

EDM Association is pleased to introduce the fifth edition of our Global Data Management Benchmark Report – PLUS, our new online Benchmark Viewer exclusively for our members!

This year’s study reflects insights from 435+ cross-industry organizations across more than 50 countries, highlighting the continued evolution of data management as a strategic, enterprise-wide capability – and a critical foundation for any AI program.

The report reveals critical data management gaps that must be addressed in our fast-moving, AI-driven era. With many AI programs struggling to drive results and deliver ROI, trusted data plays a key, foundational role to ensure greater success in AI production.

The EDM Association Benchmark aligns with the structure of DCAM (Data Management Capability Assessment Model), enabling you to compare your function to industry and peer organizations against the key components and capabilities defining mature data management.

Members: access the Benchmark Viewer by logging into EDMConnect.

Download the 2026 Benchmark Report
Image of the cover of 2026 Global Data Management Benchmark Report

2026 Data Management Benchmark at a Glance

The results of our global survey and the Global Data Management Benchmark Report illustrate that data management is now firmly established as a recognized organizational discipline, yet implementation remains uneven.

  • Across nearly all DCAM components, most organizations continue to operate within the “Developmental” or “Defined” capability ranges. This reflects meaningful progress beyond conceptual stages but also highlights that data management has not yet been fully embedded as a sustainable, business-as-usual capability in most enterprises.
  • A consistent theme is the persistent weakness in strategic foundations. Capabilities related to Data Strategy, Data Management Strategy, and Business Case for data remain among the least mature across industries. Fewer than one third of respondents report achieving advanced progress in this area.
  • The benchmark continues to show a clear maturity gap between financial services and other industries. Financial institutions consistently outperform non-financial sectors across most DCAM components.
  • Governance and organizational structures are strengthening. More than 70% of respondent organizations now report having a Chief Data Officer or equivalent role, and formal data governance functions are increasingly common.
  • The 2026 benchmark reflects a broadening and convergence of data management and analytics, particularly in response to AI. Organizations are pursuing two parallel objectives: using well-managed data to support AI initiatives and applying AI techniques to improve data management itself. Adoption patterns vary widely.
  • Gaps in education, change enablement, communications, and continuous improvement remain common.
A photo of a woman standing next to a server room and holding a laptop

2026 Benchmark Report Key Findings

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

Strategy and execution are still not in sync

Strategic foundations are the primary gap, with most organizations not reaching truly advanced, repeatable operating capability, and not yet able to to make their data and AI initiatives consistent, scalable, and embedded as business-as-usual across the organization

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

More EDM Association Data Management Benchmark Studies

View our archive of Global Data Management Benchmark Reports and other benchmark studies.