During this webinar, specialists discuss artificial intelligence (AI) fundamentals, benefits, risks, and trends. They also share a framework from The IIA that outlines leading practices for auditors to identify AI-related risks and controls.
Presenters
- Mark Maraccini, Partner, Consulting, Crowe
- Pamela Stroebel Powers, Director, Professional Guidance, Public Sector, The IIA
- Daniel Nuccio, Senior Internal Auditor, Internal Audit, City of Charlotte, NC
- Will Pellisero, IT Audit Supervisor, City of Charlotte, NC
Webinar topics
- AI is becoming increasingly prevalent in organizations, with about 60% of companies adopting it in some capacity. The public sector has been slower to adopt AI than the private sector.
- Internal auditors need to develop competency in AI to provide assurance related to AI initiatives and risks. AI can be used by internal audit to enhance efficiency and effectiveness. Examples include data analysis, audit brainstorming, report writing, preparing for presentations, and training. The IIA has developed an AI auditing framework to guide internal auditors.
- When using AI, internal auditors should focus on proper controls, data privacy, transparency, and ethics. Disclosure of AI use should be based on materiality. Generative AI models create outputs based on prompts and available data. The quality of outputs depends on the quality of training data and prompts, and outputs should be verified before use.
- Key AI risks for organizations include lack of transparency, limited visibility into AI systems, the inability to keep pace with the evolution of AI, and ethical concerns. To audit AI governance, auditors should assess policies, metrics, regulations, data sources, machine learning processes, and communication protocols. They should follow up to ensure controls adapt as AI systems evolve.
- With proper governance and controls, AI can augment human analysis and decision-making. But judgment and oversight remain essential. AI is a powerful tool when used judiciously by knowledgeable professionals, presenting benefits like process automation and enhanced analysis but also risks related to data privacy, security, bias, and misinformation. Auditors should understand the trade-offs to determine appropriate uses.
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