AI Risk Assessment

AI Risk Assessment

AI Risk assessment is an important step in any risk management process.

The process of AI Risk Assessment involves the determining of quantitative and/or qualitative values of risk related to a specific situation, and a recognized threat (also called hazard).

Quantitative AI risk assessment usually requires the calculation of two critical components of Risk:

the magnitude of the potential loss   L, and the probability p, that the loss will occur.

In auditing, AI risk assessment is a very crucial stage of any audit engagement, including GRC audit.

It is very important to understand the Entity and its Environment and also asses the Risks of any Material Inaccuracies. As an auditor, it is required that one should perform AI risk assessment procedures to obtain an understanding of the entity and its environment, including its internal control.

As part of the assessment, the auditor needs to evidence the auditor’s AI risk assessment before finding any material misrepresentation or errors in the client’s process. Subsequently, the auditor obtains initial evidence regarding the classes of events at the client and categorizes them, and then the operating effectiveness of the client’s internal controls.

In AI risk assessment, audit risk includes inherent risk, control risk and detection risk.      

Information Systems AI Risk Assessment 

Organizations assess AI risk in information systems so as to subsequently  manage them through the development and implementation of appropriate IT controls and to also enable organizations to comply with regulations that affect Management Information Systems; and thus help enterprises achieve their business objectives.

There are two methods of AI risk assessment in information systems: qualitative and quantitative.

Purely quantitative  AI risk assessments are mathematical calculations based on security metrics on the asset (system or application).

Qualitative risk assessments are performed when the organization requires that a AI risk assessment be performed:

in a relatively short time or to meet a tight budget,

a significant quantity of relevant data is not available, or

the persons performing the assessment don't have the sophisticated mathematical, financial, and AI risk assessment expertise required.

Qualitative risk assessments can be performed in a shorter period of time and with less data. Our qualitative AI risk assessments are typically performed through interviews of a sample of personnel, from all relevant groups within an organization, charged with the the asset being assessed.

Thus, qualitative AI risk assessments are descriptive versus being purely measurable in terms of numbers; but can be very effective.

In quantitative AI risk assessments, it is assessed, in terms of usually monetary figures, how much an organization could estimate to lose from an information systems asset based on the risks, threats, and vulnerabilities. Other measurements can also be done. When done in monetary terms, it then becomes possible from a financial perspective to justify expenditures to implement countermeasures to protect the asset.