AI Risk. AI Reward.

The NACD Three Rivers Chapter hosted a timely and thought-provoking virtual program exploring the rapidly evolving landscape of artificial intelligence. Featuring insights from Hart Brown (Saxum) and Harry Valetk (Buchanan, Ingersoll & Rooney), the discussion examined the risks, opportunities, and common misconceptions surrounding AI adoption in today’s business environment.

Panelists emphasized that AI is not simply another technology to be integrated into existing frameworks—it represents a fundamental shift, introducing systems capable of autonomous decision-making and unpredictable outputs. As organizations accelerate adoption, leaders must balance innovation with thoughtful governance, particularly given the speed of technological advancement and evolving regulatory expectations.

A key theme was the emergence of AI as a “digital workforce,” with companies increasingly deploying large-scale AI systems to augment human labor amid ongoing talent shortages. This shift presents significant economic opportunity but also introduces complex challenges around accountability, liability, and oversight.

The conversation highlighted critical governance considerations for boards and executives, including:

• The need for clear ownership of AI risk and decision-making
• The importance of developing internal expertise and oversight structures
• The growing risk of “cognitive offloading,” where employees over-rely on AI outputs without sufficient scrutiny
• Legal implications related to bias, errors, and regulatory compliance

Industry-specific insights, particularly in healthcare, demonstrated both the transformative potential of AI (e.g., accelerating drug development and improving patient outcomes) and the heightened risks tied to bias, regulation, and ethical use.

Panelists also underscored broader systemic challenges, including infrastructure constraints such as energy demand and data capacity, which may ultimately impact the pace of AI adoption.

The session concluded with a clear message: organizations must move beyond viewing AI as a compliance exercise and instead approach it as a strategic, enterprise-wide transformation requiring robust governance, cross-functional collaboration, and long-term investment.