Classification of AI system risk and business impact

Using Saidot, you will be able to

• Classify your AI system based on its overall risk allowing for an effective allocation of risk treatment resources.

• Analyse the business impact of the AI system to understand the expected returns better.

• Evaluate business impact together with overall risk level to compare the potential benefits of the AI system and the associated risks.

AI system risk classification refers to the perceived risk based on its specific use context, intended purpose, and the associated regulatory and business risks. Depending on the organisation's risk classification criteria, an AI system will be categorised as low-risk, medium-risk, high-risk, or prohibited. These criteria may arise from regulations and business decisions. Additionally, individual risks identified during the Risk Management process will help iteratively determine this categorisation.

The business impact of an AI system refers to the potential benefits of implementing the system and the degree to which the organisation is affected (high business impact, medium business impact or low business impact). This impact, which can be measured either quantitatively or qualitatively, represents the expected returns from investments in the AI system. It can manifest as improvements in efficiency and productivity, the introduction of new services, or other opportunities. It is important to evaluate business impact together with overall risk level as it allows for the comparison of the potential benefits of the AI system and the associated risks. This provides essential information for managing the AI governance portfolio.

Sources: Saidot proprietary