Topics for: AI and Internal Audit QualityAI and Internal Audit Quality

Focus on the human capital needed to realize AI's quality potential. What new data science skills, soft skills, and training are required for internal audit teams to effectively select, implement, and interpret results from AI tools, ensuring they remain the ultimate decision-makers?

Explore the ethical and quality challenges introduced by using AI in internal audit. How do internal auditors maintain their independence and objectivity when relying on AI-generated insights? Discuss the risks of algorithmic bias and maintaining data security while using these tools.

Discuss the specific ways AI tools (like machine learning and predictive analytics) can directly improve the quality of internal audits. How can AI help auditors achieve better risk coverage, conduct continuous auditing, and identify critical exceptions faster than traditional methods?