WCD Audit Committee Peer Exchange: Held June 9, 2026

Summary

As artificial intelligence (AI) reshapes business operations and risk landscapes, audit committees must elevate their governance responsibilities to ensure AI is deployed responsibly, ethically, and in alignment with stakeholder expectations. In addition to learning to ask management the right questions about AI controls, understanding risks related to privacy and bias, and strengthening internal audit and external assurance practices in an AI-enabled environment. On June 9, the WCD Audit Committee Peer Exchange convened to discuss how audit committees should approach oversight of AI, which included an introductory discussion with:

• Dotty Hayes, Director, Redwire Space, CoGenerate, BigBear.ai; Senior Fellow, American Leadership Forum of Silicon Valley; WCD Boston
• Dominique Shelton Leipzig, CEO, Global Data Innovation; Director, Harris & Associates
• Aisha Tahirkheli, Principal and Trusted AI Leader, KPMG US

Boards are no longer just asking if AI governance exists, they are asking how it is evidenced in practice. Peer exchange participants shared the following observations:

1. Oversight is becoming operational. Boards are looking beyond policies to understand how AI is actually deployed, seeking clearer visibility into use cases, defined system boundaries, and the controls that govern them. “The level of oversight is directly linked to the task and the risk level. How will you handle exceptions? Repetitive tasks?” asked one panelist.
2. Data is the gating factor. AI risk is increasingly tied to data quality, integrity, and readiness, shifting oversight toward how data and models are governed, tested, and monitored as they move into production. ‘Understanding the use cases also requires understanding existing successes and failures. What can you learn?” remarked one panelist.
3. Accountability is being redefined. As AI moves from supporting decisions to executing them, boards are focusing on whether oversight and exception handling align to risk and who remains accountable when AI acts. “The principles of enterprise risk management still apply,” said one panelist.

Confidence in AI will depend less on stated frameworks, and more on the ability to demonstrate that systems are operating as intended. For audit committees, this is an important and timely dialogue as governance expectations continue to evolve.