Context
A mid-sized UK financial services firm deploying AI-assisted credit decisioning and customer service automation. Facing regulatory scrutiny and enterprise customer due diligence requirements.
Challenge
No formal AI governance structure. Risk management was ad-hoc and undocumented. Procurement questionnaires from large clients were triggering escalations.
Approach
Gap assessment against ISO/IEC 42001, followed by design and implementation of a proportionate AIMS. Reused existing ISO 27001 controls where applicable.
Deliverables
- AI governance policy and accountability model
- Risk assessment methodology and registers for 4 AI systems
- Evidence pack for procurement responses
- Management review pack and operating rhythm documentation
Context
A healthcare technology provider using AI for diagnostic support and patient triage. Operating across NHS and private healthcare settings with strict data governance requirements.
Challenge
Clinical AI systems required robust governance to satisfy NHS Digital assessments and medical device considerations. Existing documentation was engineering-focused with limited governance visibility.
Approach
Built governance layer on top of existing clinical safety processes. Integrated AI risk assessment with existing clinical risk management frameworks.
Deliverables
- AI-specific risk criteria aligned with clinical safety standards
- Integrated governance model (clinical + AI oversight)
- Training materials for clinical and technical teams
- Audit readiness documentation for NHS assessments
Context
A B2B SaaS company embedding AI features across their platform. Enterprise customers increasingly requiring AI governance attestations as part of vendor assessments.
Challenge
Fast-moving product development outpacing governance. No centralised view of AI use cases or associated risks. Sales team unable to confidently respond to AI governance questions.
Approach
Rapid gap assessment followed by lightweight AIMS implementation focused on customer-facing evidence and sales enablement.
Deliverables
- AI use case inventory and risk classification
- Customer-facing AI governance summary document
- Standard responses for procurement questionnaires
- Internal playbook for product teams adding AI features
Note: These examples are illustrative and anonymised. Specific details have been generalised to protect client confidentiality. For a confidential discussion about your situation, please get in touch.
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