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.
Here is the conversation every in-house lawyer should have with an AI product before launch day.
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.
The Law Firm’s Guide To Trust Accounting And Three-Way Reconciliation
Proper trust accounting and three-way reconciliation are essential for protecting client funds and avoiding serious compliance risks. In this guide, we break down these critical processes and show how legal-specific software can help your firm stay accurate, efficient, and audit-ready.
2. Where Did You Learn This?
Every AI has a training history. You need to know whether that data came from licensed sources, open datasets, internal archives, or less reliable sources like mass web scraping.
For an in-house launch review, data provenance is not just a nice-to-have. It is often the hinge point in IP disputes, privacy claims, and regulatory investigations.
3. Which Rules Apply To You?
No AI product launches into a legal vacuum. It enters a patchwork of global and sector-specific laws. Map out every jurisdiction where the product will operate and what each requires.
Some frameworks, like the EU AI Act, focus on risk classification. Others, like financial or health care regulations, demand strict explainability and audit trails. Knowing this before launch prevents costly redesigns after the fact.
4. Can You Prove You’re Fair And Accurate?
Before launching, confirm how the AI performs across different demographic groups and scenarios. If one group consistently receives worse outcomes, that is not a mere technical issue. It is a legal and reputational liability.
Your prelaunch testing should be designed to uncover problems, not to validate optimistic assumptions.
5. Can You Explain Yourself?
If you can’t explain how an AI reached its decision, be prepared for skepticism from regulators, courts, and your own executives. Black-box models might be fine for recommending playlists, but they won’t survive scrutiny in hiring, lending, or health care contexts.
In-house counsel should ensure transparency plans are in place before launch, including technical documentation for auditors, plain-language summaries for users, and thorough internal records.
6. Who Owns The Output And The Data Trail?
Ownership and governance questions should never be left until after launch. Who controls the AI’s outputs? Can they be reused, sold, or licensed? How is input data stored, and for how long?
If external vendors are involved in the launch process, confirm their contractual obligations align with your company’s risk tolerance and compliance requirements.
7. What’s The Plan When Something Goes Wrong?
Even the most carefully prepared launch will encounter surprises. The question is not whether your AI will make an error, but how your in-house team will respond.
A solid launch plan includes escalation protocols, predrafted regulatory responses, designated decision-makers, and clear user communication strategies. These should be tested before they are needed.
Final Check Before You Launch
If your in-house team can confidently answer all seven questions, your AI product is far more likely to launch smoothly and stay out of trouble. If not, the smartest move may be to pause and fix the gaps before they become public or legal crises.
For in-house counsel, these questions are not about slowing innovation. They are about launching responsibly, building trust, and ensuring your AI can survive legal scrutiny, market pressure, and the unpredictable nature of machine learning.
When in-house lawyers lead with the right questions, the launch conversation shifts from “Can we do this?” to “How do we do this well?”
Olga V. Mack (Opens in a new window) is the CEO of TermScout (Opens in a new window), an AI-powered contract certification platform that accelerates revenue and eliminates friction by certifying contracts as fair, balanced, and market-ready. A serial CEO and legal tech executive, she previously led a company through a successful acquisition by LexisNexis. Olga is also a Fellow at CodeX, The Stanford Center for Legal Informatics (Opens in a new window), and the Generative AI Editor at law.MIT. She is a visionary executive reshaping how we law—how legal systems are built, experienced, and trusted. Olga teaches at Berkeley Law (Opens in a new window), lectures widely, and advises companies of all sizes, as well as boards and institutions. An award-winning general counsel turned builder, she also leads early-stage ventures including Virtual Gabby (Better Parenting Plan) (Opens in a new window), Product Law Hub (Opens in a new window), ESI Flow (Opens in a new window), and Notes to My (Legal) Self (Opens in a new window), each rethinking the practice and business of law through technology, data, and human-centered design. She has authored The Rise of Product Lawyers (Opens in a new window), Legal Operations in the Age of AI and Data (Opens in a new window), Blockchain Value (Opens in a new window), and Get on Board (Opens in a new window), with Visual IQ for Lawyers (ABA) forthcoming. Olga is a 6x TEDx speaker and has been recognized as a Silicon Valley Woman of Influence and an ABA Woman in Legal Tech. Her work reimagines people’s relationship with law—making it more accessible, inclusive, data-driven, and aligned with how the world actually works. She is also the host of the Notes to My (Legal) Self podcast (streaming on Spotify (Opens in a new window), Apple Podcasts (Opens in a new window), and YouTube (Opens in a new window)), and her insights regularly appear in Forbes, Bloomberg Law, Newsweek, VentureBeat, ACC Docket, and Above the Law. She earned her B.A. and J.D. from UC Berkeley. Follow her on LinkedIn (Opens in a new window) and X @olgavmack.