We help health organisations and manufacturers govern the development and use of AI safely .
Our approach combines internationally recognised AI governance standards with clinically-led risk management expertise, so your AI systems are not just compliant on paper, but safe and effective in practice.
DPM provides healthcare-specific AI governance and risk management training, covering emerging standards like ISO 42001, the EU AI Act, and AMLAS (Assurance of Machine Learning for use in Autonomous Systems).
Our two-day structured programme focuses on practical AI governance implementation with healthcare-specific risk management frameworks, helping organisations embed AI safely into real-world healthcare settings.
We support organisations through the full journey to certification — from initial gap analysis to implementation planning and ongoing maintenance.
We align everything with your existing management systems and quality processes, so AI governance becomes embedded rather than sitting as a separate, disconnected piece of paperwork.
Our team of experienced Clinical Safety Officers provide AI-specific clinical risk management support aligned with the DCB0129 and DCB0160 standards. They ensure that the particular challenges AI systems introduce are properly considered and addressed.
This work is underpinned by the Explainability Enabled Clinical Safety Framework, developed by Robert Gigiu, which brings explainability considerations directly into the clinical safety case — helping you demonstrate why your AI tools can be trusted.
Everything we do is underpinned by our AI Governance Toolkit — a tailor-made, standards-aligned framework covering the full AI governance lifecycle — from policy and committee terms of reference through to system registers, go-live checklists and ongoing monitoring.
Developed by our in-house experts, the toolkit provides the consistency organisations need to govern AI systems as they scale, without having to build every piece of documentation from scratch.
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Healthcare AI adoption is accelerating, but staff are often being left to navigate its use – and potential dangers – without clear guidance. Generic AI playbooks are insufficient for clinical contexts, and poorly governed AI poses patient safety risks and regulatory exposure.
With early, healthcare-specific AI governance:
The healthtech regulatory landscape is changing fast.
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