AI governance: A corporate counsel’s guide to doing it right

AI makes decisions at scale. If those decisions are biased, your company will make bad decisions with big consequences.

Key considerations:

• Test AI models for bias and fairness before launching them.

• Use a wide set of training data. If your AI is learning from a narrow data set, expect poor results. 

• Set up human oversight for AI decisions, particularly when they affect employment, lending, or customer support.

Why it matters: AI bias isn’t just a legal risk—it’s a brand risk. You don’t want to be the company making headlines for AI that’s gone wrong.

People don’t trust what they don’t understand. If AI is making decisions, make sure you can explain them.

• Use explainable AI (XAI). Customers and regulators will ask, “What decisions were made by AI, and what were the bases for those decisions?”

• Disclose AI usage. If AI is being used, people should know, especially when AI is deciding anything that could impact a person’s job or finances.

• Give users a way to challenge AI decisions just they can other decisions—because mistakes happen. 

Why it matters: Regulators are pushing for explainability and user control. Get ahead of it now.

AI is only as good as the data it learns from—and that data is a huge security risk.

Key considerations:

• Make sure AI systems comply with the GDPR, California Consumer Privacy Act (CCPA), and other privacy laws

• Encrypt AI data and control access. Don’t let internal teams pull AI insights without oversight. 

• Set clear data retention and deletion policies. Don’t hoard customer data you don’t need.

Why it matters: AI data breaches will cost you big in terms of fines, lawsuits, and lost customer trust.

AI isn’t a set-it-and-forget-it tool; it needs constant monitoring.

Key considerations: 

• Run regular audits. AI models drift over time, leading to bad decisions.

• Set up real-time monitoring. Track AI performance and flag anomalies. 

• Create an AI incident response plan. What happens if AI makes a catastrophic mistake?

Why it matters: AI is dynamic. If you don’t monitor it, what worked yesterday could fail today. 

If AI is part of your business, it should reflect your company’s values.

Key considerations:

• Use AI responsibly. Don’t prioritize automation over fairness.

• Make sure AI is making decisions your company is proud of. 

• Keep customers, employees, and regulators in the loop about how AI impacts them.

Why it matters: AI is shaping your company’s reputation. Make sure it’s working for you, not against you.

It might be easy to see AI governance as a roadblock, but the best companies see it as a competitive advantage. Responsible AI isn’t just about avoiding lawsuits; it’s about building trust, improving performance, and staying ahead of the curve.

You don’t need to achieve perfect AI governance overnight, but you do need to start now. Follow these steps, stay informed, and make AI accountability a core part of your business strategy.