Python and artificial intelligence are creating new opportunities to make SOX testing more efficient, consistent, and scalable. In this practical session, you will explore how to design an automated SOX testing process, including the technology, data, and Python components required to support it.
The session with Claire Worledge will examine where AI can add value, which testing activities can be automated, and where human judgment and intervention remain essential. You will also consider the implementation effort, potential cost savings, example Python code, and approaches other organizations are using to advance their SOX testing programs.
Learning Objectives
By the end of this session, participants will be able to:
- Identify opportunities to incorporate Python and AI into SOX testing.
- Describe the technology, data, and process requirements for implementing automated SOX testing.
- Evaluate the implementation effort, potential cost savings, and areas requiring human oversight.
- Recognize practical approaches organizations are using to automate SOX testing.
Duration: 60 minutes (approximate)
CPEs Available: 1
Knowledge Level: Intermediate
Category: Data Analytics
Course Content



