Control and assurance · UK teams
AI risk assessment
Identify how one AI use case could fail, who could be affected and which controls can be tested.
Understand the service
What this means in practice
An AI risk assessment should start with the task and its consequences. An inaccurate internal summary, an incorrect payment instruction and a misleading customer answer do not have the same impact. Risk depends on the information used, the people affected and what the system is allowed to do.
Temrik can facilitate a scoped assessment that turns concerns into concrete failure scenarios and acceptance tests. The goal is a decision record with owners and unresolved issues. It is not a numerical score that makes every risk disappear or a substitute for an independent security or legal assessment.
- NIST: Generative AI Profile Guidance on generative AI risks and controls.
- NIST: AI Risk Management Framework A voluntary framework for managing AI risk.
A practical workflow example
A proposed knowledge assistant handles internal procedures. The assessment includes outdated instructions, a restricted document appearing in an answer and an unsupported response to a safety question. Each scenario has an owner, a prevention or detection control and a test that can fail before deployment.
Proposed engagement
How we would approach the work
Describe the system boundary
Map inputs, retrieval sources, model providers, users and permitted actions. Record what is outside the pilot and which assumptions remain unverified.
Work through failures
Consider incorrect answers, disclosure, misuse, outages and excessive reliance. Assess impact with the people who understand the operational consequences.
Test and decide
Prioritise controls, define evidence and record residual risks. Agree who accepts the remaining uncertainty and what changes require reassessment.
Deliverables to agree in the scope
- A scoped failure-scenario register.
- A control and test plan with accountable owners.
- A decision record covering residual risks and unresolved dependencies.
Access, sample information and reviewer availability affect the plan. Any implementation, provider costs, support arrangements and acceptance criteria are agreed before work begins.
Limits worth understanding
- A risk workshop does not prove that a system is secure or suitable for every use.
- Rare and emerging failures may not appear in the initial sample; monitoring remains necessary.
Questions to bring to the first conversation
- What is the worst plausible outcome of a wrong answer?
- Can the system act externally or only prepare a draft?
- Which uncertainty would stop the pilot?
UK teams
Scope the work for your operating context.
For UK teams, include the operational owner and relevant data-protection or compliance specialists early. Distinguish this practical system-risk assessment from any formal impact assessment or statutory process the organisation may need to complete.
A starting reference for your review: ICO: AI and data protection guidance. Local obligations and deployment settings need to be assessed for the actual use case.
A focused next step
Work with Temrik.
Tell us about the workflow you want to improve and the outcome you need. We can review the context and discuss a focused assessment. Scope and price are agreed before paid work begins.