Global Perspectives and Insights: The IIA's Artificial Intelligence Auditing Framework Part II
Note: This is the second report in a three-part series. For more information, see the first report: Artificial Intelligence – Considerations for the Profession of Internal Auditing.
This special three-part edition of Global Perspectives and Insights explores internal audit’s role in Artificial Intelligence by discussing associated risks and opportunities. The paper also introduces an AI Auditing Framework comprised of six components, all set within the context of an organization’s AI strategy.
Part II
There are many terms related to AI besides machine learning, such as deep learning, image recognition, natural-language processing, cognitive computing, intelligence amplification, cognitive augmentation, machine augmented intelligence, and augmented intelligence. AI, as used in The IIA’s AI Auditing Framework (Framework), encompasses all of these concepts.
As explained in Artificial Intelligence – Considerations for the Profession of Internal Auditing, internal audit’s role in AI is to “help an organization evaluate, understand, and communicate the degree to which artificial intelligence will have an effect (negative or positive) on the organization’s ability to create value in the short, medium, or long term.”
To help internal audit fulfill this role, internal auditors can leverage The IIA’s AI Auditing Framework in providing AI-related advisory, assurance, or blended advisory/assurance services as appropriate to the organization. The Framework comprises three overarching components — AI Strategy, Governance, and the Human Factor — and seven elements: Cyber Resilience; AI Competencies; Data Quality; Data Architecture & Infrastructure; Measuring Performance; Ethics; and The Black Box.
