Generative AI is transforming industries, from content creation to customer support. But as companies race to integrate AI into their products, AI risks for product counsel are evolving just as quickly.
Most discussions focus on data privacy, copyright, and bias. However, there’s a growing risk that’s often overlooked: When AI-generated content starts making business decisions, who is responsible when things go wrong?
When AI Becomes a Decision-Maker: Legal Implications for Product Counsel
A human using AI to generate marketing copy or summarize documents is one thing. But what happens when AI autonomously sets prices, approves transactions, or prioritizes certain users over others?
The legal questions shift from intellectual property concerns to AI risks for product counsel. This includes contractual liability, regulatory compliance, and even corporate governance.
Companies might assume their AI systems are just assistants. Yet regulators may see them differently, especially if the AI’s decisions impact consumer rights, competition, or financial transactions.
Key Risks Product Counsel Should Be Watching
Some jurisdictions are already debating whether AI-driven decisions should be legally attributed to the company, the developers, or even the AI itself. If AI determines creditworthiness, sets wages, or makes hiring decisions, who is ultimately liable for bias, discrimination, or unfair practices? As AI systems take on more responsibility, the traditional boundaries of corporate liability and accountability are becoming increasingly blurred.
Contractual and Regulatory Blind Spots in AI Decision-Making
AI risks for product counsel include the fact that AI-generated content doesn’t always fit neatly into existing legal frameworks. Standard contracts assume human intent. But what if an AI-generated response misrepresents pricing, violates a user agreement, or breaches a regulatory requirement? Companies must ask whether they bear full responsibility for AI-driven mistakes. Alternatively, should new frameworks be developed to account for AI’s role in decision-making?
Compliance Can’t Be an Afterthought
AI decision-making can inadvertently violate anti-discrimination laws, consumer protection statutes, or even competition rules. An AI-driven pricing model, for example, may adjust costs based on consumer behavior in ways regulators see as predatory. Without proactive oversight, companies could face significant fines and reputational damage. Compliance must be built into AI development from the start, not treated as a last-minute legal check.
How Product Counsel Can Get Ahead of AI Legal Risks
Generative AI is evolving faster than the legal frameworks designed to regulate it. Product counsel needs to be proactive, ensuring that AI’s role in business decisions is carefully considered.
Understanding whether AI is merely assisting or autonomously influencing company policies is the first step. Legal teams must evaluate contracts and policies to ensure they adequately address AI risks for product counsel. This includes liability, indemnification, and regulatory compliance. If current agreements don’t account for AI-driven mistakes, companies may need to rethink their approach.
Engaging regulators early is also key. AI regulation is coming, and businesses that take a proactive role in shaping best practices will be better positioned than those caught off guard. Rather than waiting for new laws to dictate compliance, legal teams should work alongside industry leaders, policymakers, and internal stakeholders. This collaboration helps define ethical and responsible AI practices.
The Future of AI and Legal Strategy
AI isn’t just another product feature—it’s a fundamental shift in how businesses operate. Legal teams must move beyond traditional risk mitigation. They must take an active role in AI governance, compliance, and business ethics. The companies that integrate legal strategy into AI development from the outset will be the ones best equipped to navigate the challenges ahead.
How is your legal team preparing for the challenges of AI-driven decision-making?
