Risk assessment in the context of AI refers to the structured process of identifying, evaluating, and prioritising potential harms or failures associated with an AI system’s design, deployment, and operation. It is a central component of AI assurance, enabling organisations to systematically manage uncertainties and take proactive steps to mitigate negative outcomes.

AI risk assessments can address a wide spectrum of risk types, including:

• Technical risks: such as performance failures, adversarial vulnerabilities, or model drift

• Legal and regulatory risks: including data privacy violations, non-compliance with standards, or unauthorised use

• Ethical risks: such as bias, unfair treatment, or opacity in decision-making

• Operational risks: like system downtime, human error in oversight, or inadequate training

• Reputational and societal risks: including erosion of public trust or unintended social consequences

The goal of an AI risk assessment is to:

• Understand the full context in which an AI system will operate

• Identify where and how it may cause harm or underperform

• Determine likelihood and impact of such events

• Recommend and implement risk mitigation strategies

Effective assurance involves both qualitative and quantitative risk analysis. Techniques may include scenario planning, stakeholder consultation, red teaming exercises, and empirical testing. Outputs from these analyses inform mitigation actions such as redesign, additional testing, restricted deployment, or oversight enhancements.

Risk assessments are often required as part of regulatory compliance, such as under the EU AI Act (where impact and risk assessments are mandated for high-risk systems), or national AI governance policies. They are also increasingly embedded in AI procurement processes.

In high-stakes environments — such as defence, public health, or critical infrastructure — risk assessments are essential to avoid operational failures, ensure ethical deployment, and support informed decision-making. Assurance providers may conduct independent risk reviews to validate that appropriate measures are in place.