Managing AI risks without slowing growth
AI is no longer a future project but an operational reality, already embedded in many companies through third-party tools that often operate with little oversight. Establishing effective governance and oversight isn’t about slowing innovation, it’s about showing diligence and leadership. Regulators, investors and customers increasingly expect responsible use of AI. Applying the same discipline you bring to financial reporting can help fulfill fiduciary duties and protect upside. Business leaders who act now will be better positioned to avoid costly compliance missteps and protect their reputations as AI adoption accelerates.
Focus on business risks, not technical glitches
Business leaders don’t need to know how models are built. They need visibility into how AI affects the business, who owns it and how issues are escalated. AI risks usually resemble traditional failures—just faster. Here are six risks leaders must manage:
- Bad Decisions (Operational): AI is only as good as its data. If it sets prices or manages inventory without checkpoints, a simple input error can lead to significant financial losses.
- Fraud (Cyber): Hackers use deepfake voices to impersonate bosses and steal money. Training isn’t enough; enforce call-back rules for unusual payments.
- Over-Promising (Regulatory): Avoid “AI washing.” If marketing claims AI-driven or unbiased processes, they have documentation to back them up or risk an audit.
- Hiring Bias (Employment): If AI screens resumes or evaluates staff, you’re responsible for its biases. Be ready to explain and defend decisions.
- Data Leaks (Contractual): Many AI tools learn from your input. Without appropriate input and review procedures, proprietary information could be disclosed in public outputs.
- Blame Game (Reputational): Customers hate it when companies blame a computer. Maintain trust with a clear human owner who fixes mistakes fast.
Contracts and insurance
Most AI comes from vendors, and risks hide in the fine print of their contracts. Require audit rights, liability protections and clear data-use terms. Similarly, you must review your Directors & Officers, Cyber and other policies to ensure they cover AI-related claims—coverage gaps can turn minor errors into significant financial exposure.
A right-sized governance plan
Most companies don’t need an AI department—just a tiered approach:
- Phase 1: Add AI to audit agendas and require a report on usage and accountability.
- Phase 2: As adoption grows, form a cross-functional team to vet tools.
- Phase 3: If AI constitutes a core business function, move to independent testing and require board reporting.
AI oversight isn’t optional—it’s a fiduciary duty that protects growth and reputation. Critically, the goal of AI governance isn’t bureaucracy; it’s a proportionate structure—enough to manage risk and demonstrate oversight without slowing business. Not sure where to start? Begin with an AI risk inventory—what tools you use, who owns them and what controls exist.
Creating a record to strengthen legal protections
AI governance must be proactive and documented to invoke the Business Judgment Rule and demonstrate that leadership acted in good faith. A paper trail can be risky if flaws lack context. To solve this, engage legal counsel to direct AI risk assessments under attorney-client privilege. This creates a safe sandbox for candid evaluations and informed decisions within a secure legal perimeter.
The bottom line
AI can drive speed and margin, but without ownership and guardrails, it introduces familiar risks—compliance failures, data exposure, vendor breakdowns and reputational damage. Combine visibility with legal privilege to ensure business judgment is informed and protected.
Successful boards build accountability, not technical expertise. Start your AI oversight today—add it to your next board agenda and protect your business before risks escalate.