Trust, Security Resilience: Governing AI in Healthcare with Confidence
- Thibault Williams
- Jun 11, 2025
- 4 min read
Updated: Jun 16, 2025
How international standards and NHS principles shape the future of safe, accountable AI in health.
The potential for artificial intelligence (AI) to transform healthcare is no longer hypothetical. From fall prediction in elderly care to population-level disease modelling, AI systems are already shaping diagnoses, triage, and resource planning.
But as these systems begin to touch sensitive patient data and influence care pathways, they raise an urgent question: How do we ensure these technologies are not just effective - but safe, compliant, and trustworthy?
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At TMW Resilience, we believe the answer lies in operationalising three foundational principles:
Secure by design
Compliant by design
Resilient by design
And the best way to do that? Structured adherence to standards - not just as paperwork, but as living systems.
What is “Reasonable AI” in Healthcare?
The NHS recently released its updated AI Code of Conduct for health and care technologies. This guidance lays out ten principles for developers, suppliers, and implementers of AI in healthcare.
It emphasises:
Transparency and explainability
Safety, efficacy, and data protection
Robust evidence and stakeholder involvement
Bias mitigation and equality of access
Crucially, the Code is not a checklist - it’s a values-led framework. It asks not only what an AI system does, but how it was built, who it impacts, and whether it can be trusted in high-stakes environments.
That’s why at TMW Resilience, we champion the idea of “Reasonable AI” - AI that is not just high-performing, but accountable, auditable, and adaptive. And to achieve that, we use two powerful international standards:
ISO/IEC 42001: The first management system standard for artificial intelligence
ISO/IEC 27001: The global benchmark for information security
Published in December 2023, ISO/IEC 42001 is the world’s first AI-specific management system standard. It provides a framework for:
Defining AI policies, roles, and responsibilities
Managing AI-specific risks (like model drift or unexplainable outputs)
Embedding controls across data use, model training, testing, deployment, and ongoing monitoring
Ensuring traceability, transparency, and ethical alignment
ISO 42001 turns good intentions into operational controls.
Key Components Aligned to Healthcare
Area How ISO 42001 Applies in Health
Context of Use Models must be evaluated based on how and where they’re deployed (e.g. clinical triage vs. population screening) Human Oversight Defines clear accountability models between developers, clinical teams, and governance boards Ethics & Risk Formalises ethical impact assessments and risk mitigation planning Model Management Enforces documentation of model training, updates, performance testing, and validation
When aligned with NHS AI Code principles, 42001 enables the development of AI that is explainable, safe, and suited to public service delivery.
ISO/IEC 27001: Securing the Foundation
AI governance doesn’t stop at the model - it must also protect the data infrastructure around it. That’s where ISO/IEC 27001 comes in.
This standard sets out how to build and operate an Information Security Management System (ISMS). It ensures that sensitive health data is:
Stored securely
Accessed only by authorised parties
Handled in line with GDPR and the UK Data Protection Act
Monitored for breaches, misuse, and unauthorised processing
TMW Resilience implements ISO/IEC 27001 controls alongside 42001—ensuring that AI governance and data protection are fully integrated.
From Principles to Practice: The Three Pillars of Reasonable AI
Here’s how these standards enable our secure, compliant, and resilient approach.
Secure by Design
Security isn’t a bolt-on - it’s a baseline. In healthcare, this means safeguarding not just systems, but lives.
We implement data classification and minimisation from the start - collecting only what’s needed for the defined AI task
Access is controlled via role-based permissions, and every access event is logged
AI outputs are stored and transmitted with end-to-end encryption, aligned with NHS Digital standards
Our systems undergo regular penetration testing and threat modelling, built into ISO 27001 protocols
Outcome: Stakeholders can trust that AI does not expose patients to new vectors of digital harm.
Compliant by Design
True compliance goes beyond the law - it reflects respect for people and their rights.
We implement Data Protection Impact Assessments (DPIAs) for all AI applications, in line with UK GDPR
All models are explainable by design - with mechanisms to support patient-facing explanations and clinical review.
We document training data lineage, including source, purpose, and validation
Our clients receive full audit trails and conformance mapping to NHS AI Code, ISO 42001, and ICO guidance
Outcome: AI systems don’t just comply with policy they earn legitimacy with regulators, clinicians, and the public.
Resilient by Design
Healthcare is dynamic. AI must be resilient to change, uncertainty, and evolving risks.
Our governance systems support model drift monitoring, triggering revalidation if performance degrades
We maintain version control and rollback mechanisms for AI models and data sets
Regular retraining schedules are documented and linked to risk thresholds
Governance is continuous, not one-time - each project has assigned roles for AI ownership and escalation
Outcome: AI remains functional, ethical, and safe - even as data shifts, regulations evolve, or deployment environments change.
Why NHS and Public-Sector Stakeholders Should Care
Healthcare AI can’t afford to move fast and break things. What it needs is:
Rigorous oversight
Real-world responsibility
Sustainable scalability
Whether it’s working with local authorities on predictive fall prevention, or supporting regional data infrastructure to power preventative health outreach, TMW Resilience brings a proven model to the table - combining global standards with sector-specific nuance.
AI in Healthcare is a Governance Challenge First
If we want AI to improve health outcomes, reduce inequality, and support overstretched services, we have to do the hard governance work now.
TMW Resilience is ready.
With certified lead implementers in ISO/IEC 42001 and deep experience in ISO/IEC 27001, we help health and care organisations govern AI with the rigour it demands—and the public deserves.
Let’s build Reasonable AI. Together.
Want to see how this works in practice? Let’s talk.
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