Rethinking data maturity in the age of AI

What separates AI-ready data teams from the rest?

We surveyed data leaders to uncover what it takes to build data operations that scale with AI.

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Rethinking data maturity in the age of AI: Data Report 2026

The findings at a glance

Scalability matters most

The new definition of data maturity is scalability

The new test of data maturity isn’t just whether your team can deliver, but in the age of increased data demand from AI, it’s whether your operating model can change and adapt without adding proportional effort, risk and delay every time. 

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What else you'll get from the report

Understand the common barriers holding organisations back, from manual work and technical debt to weak governance and operational control.

Discover how automation, reuse, observability and embedded controls help organisations scale data operations with greater confidence. 

Use the report's maturity model and 90-day action plan to identify priorities and start moving towards scalable, AI-ready data operations.

See how AI is changing the definition of data maturity — and why scalability is becoming the new benchmark. 

Rethinking data maturity in the age of AI

 

How are teams building AI-ready data operations that scale?

Over 200+ organisations across the US and UK told us how they're closing the gap between AI ambition and data readiness in 2026.
What else you'll find inside the report:
Rethinking data maturity in the age of AI: Data Report 2026
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Data integration with CloverDX

About CloverDX

CloverDX combines powerful data integration with AI that accelerates every stage of the work.

Data engineering and analytics teams in financial services, insurance, healthcare, government, and retail use it to manage complex, high-volume data while keeping visibility and control over how that data moves through their systems.

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