Overview

Artificial Intelligence (AI) is transforming healthcare, from diagnostics and predictive analytics to improving operational efficiency. But with huge potential comes significant risk—bias, safety concerns, and accountability gaps. Robust governance is essential to ensure AI is used safely, ethically, and effectively.

This session explored how organisations can embed AI governance frameworks within health systems, aligning with NHS assurance requirements and building trust through transparency and accountability.

Andrew Bowdler, Principal Data Analyst, MIAA covered AI Governance – Frameworks and Assurance

• Why AI Governance Matters: Balancing opportunities with risks
• Core Principles: Safety, transparency, accountability, and ethics
• NHS Context: Frameworks and regulations shaping AI governance
• Practical Steps: Implementing governance from policy to operational oversight
• Aligning with Assurance: Meeting NHS requirements and making governance continuous
• Building Trust: Stakeholder engagement and transparency
• Case Study: AI governance in action through a radiology pilot project
• Challenges & Lessons Learned: Common obstacles and practical solutions

Richard Parker, Hill Dickinson LLP covered Legal Responsibilities and Accountability in AI

• Summary of the UK AI Regulation Landscape
• Data (Use and Access) Act 2025
• Automated Decision‑Making (ADM) current position under UK GDPR
• The new position under DUAA 2025
• AI as a Medical Device (AIaMD)
• Information Standards DCB0129 and DCB0160

Watch the session

 AI Governance in health: Building Trust, Assurance & Accountability, Andrew Bowdler, MIAA