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OECD report AI in healthcare

OECD publishes report on responsible scale of AI in healthcare

By i~HD

October 08, 2026

The Organisation for Economic for Co-operation and Development (OECD) has shared a proceeding report on AI in healthcare that was drafted during its Responsible Scale of AI in Health conference in Madrid, Spain in May 2026. The European Institute for Innovation through Health Data (i~HD) was part of OECD's International AI Expert Group that drafted this Expert-Led Madrid Action Plan (EL-MAD).

Expert-Led Madrid Action Plan

i~HD participated in the OECD International AI in Health Expert Group that was officially formed in May 2024. After 18 months of discussions and fora, the group emphasised that the primary constraint on the benefits of AI in health lies more in system-wide diffusion at scale, including across borders, rather than in technological potential.

The Expert Group drafted an action plan that was presented and discussed during the "Responsible Scale of AI in Health" conference in Madrid, Spain on 28-29 May 2026, co-organised by the OECD and the Spanish Ministry of Health. i~HD President Dipak Kalra moderated one of the panel discussions in this event, which brought together 142 experts from 34 countries and 35 partner organisations.

The discussions during the conference paved the way towards the Expert-Led Madrid Action Plan (EL-MAP), a core section in the OECD proceedings report published in October 2026. This action plan outlines ten concrete action points addressing the urgency of balancing the transformations in healthcare facilitated by AI with the risks and challenges posed by the technology. 

Al is already transforming health. It helps to detect diseases earlier, improve treatments, ease workloads, streamline operations, protect public health, and stimulate innovation. It also brings new risks, challenges, errors, legal and privacy concerns, and unclear responsibilities. Acting together will support transformation that unlocks human benefits while earning trust.

OECD International AI in Health Expert Group

EL-MAP Action Points

The EL-MAP lists ten action points, organised thematically into three categories to guide collective action:

  • Establish and sustain trust
  • Strengthen foundations
  • Develop economic and financial models
  • Establish and sustain trust
  • Strengthen foundations
  • Develop economic and financial models

Establish and sustain trust

1. Co-design use cases for AI-powered, person-centric learning health systems (Co-design of use cases)

2. Co-develop competencies and capacities to work with AI (Capacity building)

3. Co-facilitate multi-party co‑operation and partnerships (Collaboration and partnerships)

Strengthen foundations

4. Identify leading practices to oversee and lead the integration of AI in health (Leadership)

5. Develop baseline policies that support the effective scale of AI in health (Policy)

6. Develop baseline policies, processes, and approvals for the full AI in health lifecycle (Life Cycle)

7. Strengthen data and digital infrastructure with protection and to support scale (Infrastructure)

8. Enable effective adaptability to emerging capabilities (Adaptability)

Develop economic and financial models

9. Develop model for economic returns from AI in health (Economics)

10. Develop considerations for financial management related to AI in health (Financing)

AI guardrails

i~HD's open letter on AI guardrails

The OECD report, especially the action points of the EL-MAP, resonates with an open letter published by i~HD calling for the development of guardrails in AI healthcare, together with the development of the technology and its applications. The open letter also emphasises the need for safe and trustworthy use of AI, human oversight, capacity building and continuous engagement with stakeholders

Read the open letter here

Moving forward

The expert group and international organisations plan to collaborate on how and when to proceed with the action plan and to address the urgency highlighted in the report.

Read the full OECD report here