Answer yes if your organisation has conducted and documented a regulatory compliance and security risk assessment for each AI or AI-supported service you provide. This should consider how the service operates and is secured against requirements such as the EU AI Act or the OWASP Top 10 for LLM, along with output accuracy, bias countermeasures, abuse prevention, and the risk of IP or copyright infringement claims from AI-generated output. Set clear security criteria to test against before deployment, and revisit the assessment periodically using monitoring data and feedback rather than treating it as a one-off exercise. Upload supporting documents evidencing the assessment, or describe it in the notes section.
What is the control?
Information Security is in large parts about risk management. Quite simply, we improve security by removing risks as best we can within a certain scope and level or resource.
The first step to being able to do so is assessing what risk your IT estate faces. Your organisation should therefore have a policy stating that risk assessments are to be performed as part of your risk management strategy. This policy should also define the scopes of these assessments.
Why should I have it?
Any significant change to your environment — including external factors such as changes to legislation, best practice guidance, emerging threats, and changes of processing scope — should be subject to an assessment to determine its impact. Few changes are potentially as significant as those as services which change information processing, such as the use of AI models and services.
Where your organisation has applied AI-supported services to client data, it is important to evaluate the risks of disclosing your client’s data and information to each of those external services.
Use of Generative AI and Machine Learning is subject to regulation in some jurisdictions. In addition, the services and models have inherent vulnerabilities and potential for exploitation, undermining their integrity and the results of processing. Consideration should be given to the use of those processing results, including accuracy and risk of inherent bias that may influence your client’s decision-making and operations.
Adapt your risk management policy and process to include AI models in scope. The policy should dictate the circumstances and scope of risk assessment activities, as well as prescribe that your risk management processes identify risks - including what systems or data may be at risk, from what threats, because of what particular vulnerabilities, etc. — then evaluate those risks and lead to decisions on what controls or corrective measures should be put in place.
Record and track all of the above for accountability and auditability reasons, and review as necessary as part of ongoing risk management and continuous improvement efforts.
There are numerous consultancies or individual consultants that will be able to assist in crafting a policy and process that meets your business and technical requirements.
The following references may be helpful:
Standard: ISO/IEC 42001:2023 Information Technology — Artificial Intelligence — Management System
Codes of practice: