Research Transformation 2026: Strategic priorities for research leaders

Beyond awareness. Into execution.

From theory to reality: The AI and Open Research landscape

Your institution has the policies. It has the principles. The question is whether it has the infrastructure, the incentives, and the culture to make any of it work.

Crucially, AI is no longer an emerging technology on the horizon of research practice. It is the present operating environment. AI tools are now embedded across research workflows and institutions are actively managing the opportunities and risks this brings.

This 2026 update draws on the State of Open Data 2025, a report providing 10 years of longitudinal evidence from 4,700+ responses across 151 countries.

What the data tells us

Awareness has scaled, implementation lags
FAIR principles are widely known, but consistently applying them in practice remains a challenge across the sector.
The credit gap remains the biggest structural barrier
Most researchers still feel their data-sharing contributions go unrecognised, and career incentives have yet to catch up.
AI is accelerating research, but exposing new risks
AI adoption jumped nearly 10 percentage points in a single year, bringing real efficiency gains, and real questions about integrity and skills.
Collaboration is expanding, but under strain
More researchers are working across sectors and borders, but funding gaps and security concerns are limiting what that collaboration can achieve.
Research security is rising as a strategic priority
Institutions are spending more time on security, but few yet have the expertise, resources or cultural alignment to manage it proactively.

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Structural tensions

Awareness vs. implementation
Everyone knows FAIR. Almost no one has built it into daily practice.
Innovation vs. incentive structures
Researchers are innovating faster than career incentives can keep up.
Openness vs. security & trust
Open data without security and trust is a liability, not a milestone.

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What comes next

The institutions pulling ahead aren’t waiting for better policy. They’re connecting what they already have, data, infrastructure, incentives, into something that actually works together. The ones that don’t will keep losing researchers, funders, and credibility to the ones that do.

From awareness to execution
Embed open practices into everyday workflows: not as a policy ask, but as a supported, low-friction default.
From measurement to meaningful insight
Move beyond metrics dashboards: connect research data across the lifecycle to drive real strategic decisions.
From openness alone to openness with trust
Accessibility and responsibility must advance together: openness that ignores security and privacy is not sustainable.

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