This course explores the integration of Artificial Intelligence (AI) in Auditing. Beginning with AI's role in business, it delves into its complexities, especially the "black box" challenge, making model verification difficult for auditors.

While highlighting the myriad opportunities AI offers, such as enhanced data analysis and predictive risk assessments, the course emphasizes the auditor's responsibility in using AI-generated evidence. It concludes by addressing strategies for audit firms to optimally use AI, ensuring ethical considerations and adherence to evolving regulations.

The course underscores the balance between leveraging AI innovation and maintaining auditing integrity.

During this free session we will have a discussion on the use of AI in our audits and how we can be prepared.

1. Introduction
2. Brief overview of AI and its growing role in the business world
3. How AI is changing the landscape of auditing.
4. The 'Black Pit' of AI
5. Definition and Explanation:
6. AI models, especially deep learning, have millions of parameters that can be hard to interpret
7. The concept of a black box – understanding inputs and outputs but not the internal workings Implications for Auditing:
8. Challenges in verifying the accuracy and reliability of AI models
9. Difficulty in understanding and validating assumptions, biases, and decision-making processes of AI models.
10. Opportunities Introduced by AI
11. Data Analysis:
12. Handling large volumes of data with ease
13. Advanced data analytics for detecting anomalies or fraud
14. Automation:
15. Automated transaction testing
16. Reducing manual, repetitive tasks
17. Predictive Capabilities:
18. Predictive analysis for risk assessments
19. Enhancing audit quality by predicting potential audit risks.
20. End Responsibility and Acceptable Evidence
21. Traditional Evidence vs. AI-Generated Evidence:
22. Discussing the nature of evidence produced by AI vs. traditional methods
23. Responsibility:
24. The auditor's responsibility to understand the tools they use, including AI
25. The challenge of determining responsibility when errors occur
26. Acceptability of AI-generated Evidence:
27. Ensuring AI tools and processes are robust and reliable.
28. All Audit Managers, Senior Managers, Directors and Partners will benefit from attending this session.