"Launching an AI product without a rigorous in-house review is like sending a driverless car onto the highway without checking the brakes. It might work perfectly. Until it doesn't. The most successful AI launches I've seen share a common thread: in-house counsel who know exactly what to ask before anyone hits "go." These questions don't just uncover compliance gaps. They often help shape the product into something more ethical, more defensible, and more competitive."
"1. What Exactly Are You? Before you can manage launch risks, you need a plain-language description of the AI system itself. Is it generating new content or making predictions? What decisions or outputs will it influence? What business need is it addressing? Too often, in-house teams hear about "the AI" in vague, hype-filled terms. Without clarity on the model's type and scope, your launch strategy is shooting in the dark."
Before launching an AI product, teams must produce a plain-language description of the system, its outputs, influence on decisions, and the business need it addresses. Teams must document training data provenance, distinguishing licensed sources, open datasets, internal archives, or mass web scraping to anticipate IP, privacy, and regulatory issues. The product must be mapped against applicable global and sector-specific laws, including risk classifications and explainability or audit requirements where relevant. Teams must validate performance and fairness across demographic groups and scenarios. Early legal engagement can identify compliance gaps, reduce redesign costs, and improve ethical defensibility and market competitiveness.
Read at Above the Law
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