AI, Data & Intelligence
AI Governance
The operating model that controls AI across the organisation: an AI system inventory, risk classification, approval gates, committee structures, policies and the evidence trail regulators and auditors expect.
Capability overview
What ai governance involves
AI governance answers practical questions: What AI systems do we run or buy? Which are high risk? Who approved them, on what evidence, and who checks they still behave as intended? Without that machinery, AI adoption either stalls under blanket caution or proceeds without anyone knowing the exposure.
We design governance proportionate to risk, so a meeting summariser does not face the same scrutiny as a claims decision model. Structures align with ISO/IEC 42001, the international standard for AI management systems, and the govern function of the NIST AI Risk Management Framework, which makes later certification or regulatory review far easier.
What is included
Governance components
AI system inventory
A register of internally built and third-party AI systems with owner, purpose, data used, risk tier and status.
Risk tiering
Criteria that classify systems by impact on individuals, financial exposure, autonomy and regulatory relevance, each tier with required controls.
Lifecycle approval gates
Checkpoints at design, pre-deployment and periodic review, with defined evidence such as test results and impact assessments.
Committees and roles
An AI governance council with clear terms of reference, escalation paths and links to existing risk and data protection functions.
Third-party AI controls
Procurement questions and contract clauses for vendors whose products include AI features.
How we work
How we deliver ai governance
Baseline assessment
Existing risk, data protection, model risk and IT governance processes reviewed to reuse what already works.
Operating model design
Roles, forums, tiers and gates drafted and tested against a sample of real AI use cases.
Policy and templates
AI policy, intake forms, impact assessment templates and approval records produced.
Tooling setup
Inventory and workflow configured in an existing GRC platform or a lightweight dedicated tool.
First governance cycle
Current systems registered and tiered, and the first council meetings facilitated until the rhythm is established.
Related capabilities
Related capabilities in Responsible AI & AI Security
AI Risk Management
Identification, assessment and treatment of risks from specific AI systems, including errors, bias, misuse, security, privacy and third-party dependency, documented in a way risk committees can act on.
AI Security Assessments
Independent security reviews of AI systems end to end, covering data pipelines, training infrastructure, model supply chain, inference APIs and integrations, mapped against MITRE ATLAS attack techniques.
AI Model Security
Protection of machine learning models themselves against theft, tampering, poisoning, adversarial inputs and malicious model files, from training through registry to production serving.
LLM Security
Runtime security for applications built on large language models: controls against prompt injection, sensitive data disclosure, insecure output handling, excessive agency and unbounded consumption.
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Where this applies
Healthcare & Life Sciences
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Banking, Financial Services & Insurance
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Questions & answers
Questions about AI Governance
Cannot find what you need? Our team responds to technical and commercial questions within one business day.
Ask a questionProportionate governance usually speeds it up. Low-risk uses pass through a quick self-assessment, and teams building higher-risk systems know the evidence required in advance instead of facing late objections.
Not necessarily. Aligning with the standard gives a recognised structure. Certification is worth pursuing when customers, regulators or tenders ask for independent assurance.
Through procurement due diligence, contract terms on data use and model changes, and registering those features in the inventory with a business owner responsible for their use.
Design and rollout are fixed-price phases based on organisation size and the number of AI systems. Ongoing governance support, such as council facilitation, can be a monthly retainer.
Next step
Discuss ai governance with Acmez
Share what you need to change, build, integrate or support. We will map the practical next step.