Leveraging AI-Driven Control Management: Maximize risk resources to scale and optimize controls
Time spent testing, monitoring, reporting, and updating controls is a resource-intensive practice for most enterprises regardless of your program’s maturity. While Artificial Intelligence (AI) cannot analyze risk with the same judgment and interpretation as a human, there are several specific use cases where AI and automation can help augment and maximize your efforts to consolidate, coordinate, and communicate risk insights. In this session, we’ll recognize some of the risks of AI and explore how AI-driven control management can help streamline data processing and preparation. Internal auditors, risk managers and control owners can apply AI to analyze risk scenarios, report business outcomes, and optimize their control management processes to protect your organization better.
In this session, you’ll learn how to:
- Leverage pre-mapped controls based on standard practices across leading frameworks and practices
- Automatically identify and suggest controls to fulfill new business requirements, address control gaps, or complement existing practices
- Discuss the necessary data foundation and infrastructure to enable reliable AI processing
GRC Offering Lead