AI RISK ASSESSMENT

Identify AI risks. Prioritise the controls that matter.

GLIE Legal helps organisations identify, assess and prioritise the risks associated with specific AI systems and use cases.

We connect legal, organisational and operational considerations with practical risk treatment, defined responsibilities and documented decisions. The aim is a clearer basis for deciding whether, and under what conditions, an AI use case should proceed.

Discuss your AI risk assessment

Who this service is for

For organisations that need a structured assessment before introducing AI, expanding an existing use case or reviewing the adequacy of current safeguards.

Businesses assessing AI tools before procurement or deployment.
Product and technology teams developing or integrating AI-enabled services.
Legal, compliance, risk and operational teams reviewing sensitive or business-critical uses.
Organisations seeking a documented basis for approval, escalation and ongoing monitoring.

From individual concerns to a structured risk picture

The assessment is tailored to the intended use, the people and processes affected, and the evidence available within the agreed scope.

Use-case context and boundaries

Define the intended purpose, users, affected stakeholders, decision points and operational setting, including dependencies on suppliers and other systems.

Risk and impact identification

Identify potential adverse outcomes for people and the organisation, considering relevant legal, data, fairness, oversight, reliability and operational concerns.

Evaluation and prioritisation

Assess likelihood and severity using agreed criteria. Record existing safeguards, evidence limitations and uncertainty to establish a reasoned order of priority.

Human oversight and accountability

Review who can approve, challenge, override or stop the use of AI, and identify gaps in responsibilities, escalation routes and decision-making authority.

Risk treatment planning

Propose proportionate measures to avoid, reduce or otherwise address identified risks, with proposed owners and implementation priorities. Record residual risks for authorised decision-makers.

Monitoring and reassessment

Define review points and triggers for reassessment, such as changes in purpose, data, supplier, system behaviour or the conditions of deployment.

Clear evidence for risk-informed decisions

Depending on the agreed scope, deliverables may include:

A use-case scope and context statement.
A documented assessment methodology and evaluation criteria.
An AI risk register with prioritised findings.
A risk treatment plan with proposed control owners.
A residual risk and decision log.
A monitoring and reassessment schedule.
A management briefing on key risks, information gaps and next steps.

Findings distinguish between documented evidence, stakeholder statements and assumptions. Information gaps and any need for specialist technical validation are recorded explicitly.

How the engagement works

Define the assessment

Agree the use cases, boundaries, stakeholders, available evidence and decisions the assessment needs to support.
Gather evidence and identify risks

Review relevant documentation and work with stakeholders to identify risk scenarios, existing safeguards and information gaps.
Evaluate and plan treatment

Apply the agreed criteria, prioritise findings and develop practical treatment actions with proposed responsibilities.
Support decisions and follow-up

Present the assessment, document outstanding decisions and define monitoring, escalation and reassessment arrangements.

A defined assessment. Clear limits.

This service provides a structured advisory assessment within an agreed scope. It is not a certification, a guarantee of compliance or a guarantee that an AI system is safe or free from adverse outcomes.

Technical model testing, cybersecurity testing, independent assurance, formal conformity assessment and specialist impact assessments are not included unless expressly agreed. Where additional expertise or evidence is needed, this is identified in the findings.

Final decisions on deployment, risk acceptance and operational controls remain with the organisation’s authorised decision-makers.