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We post articles that get to the point. Covering topics in law, business, technology, innovation and startups. Each article is based on questions we receive from entrepreneurs, investors and high-growth companies we work with.

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AI Risk Hides in Plain Sight

 

In today’s technology deals (both VC and M&A), AI issues surface even when the company isn’t an “AI company.” From code generation to customer data, artificial intelligence now threads through daily operations, product design, and compliance risk. Ignoring it can create hidden liabilities. It is also creating opportunities for companies to demonstrate robust enterprise value through high-caliber compliance to investors and buyers.

Core Insights

  • AI-assisted code, uncertain ownership. Developers and operators increasingly use AI tools for coding. Those tools can inadvertently reproduce licensed or copyrighted material. Diligence should test whether policies exist around AI-generated code, and seek to confirm that all resulting IP is verifiably owned and assignable.

  • Data exposure through AI tools. Engineers and marketers often paste proprietary code, client data, or sensitive business information into public AI systems. That creates major confidentiality and data protection risk. Buyers/Investors should confirm that no sensitive data has been shared with third-party AI providers; Companies should ensure robust use policies are established to protect against problematic disclosure; Personnel should be comprehensively trained on risks, best practices, and compliance.

  • Governance is not just for the board room. Regulators expect companies to have internal AI use policies, vendor standards, and audit trails. Those aren’t just paperwork, they demonstrate maturity and reduce diligence friction when laws or investor expectations evolve.

  • Privacy law meets machine learning. If user data trains or fine-tunes any internal models, the company may be crossing into regulated territory. Confirm compliance with privacy consents, cross-border transfer rules, and modification/deletion rights. AI does not excuse privacy lapses.

  • Contracts need to catch up. Modern deal terms should cover AI-related representations: lawful data sourcing, transparency, and IP ownership of model outputs. A single outdated customer contract can expose the buyer to unforeseen liability or indemnity claims.

  • Reputation risk compounds fast. AI exaggerations in marketing or product claims can backfire with regulators, investors, buyers, and customers. Scrutinize how “AI-powered” features are described. Credibility matters as much as capability.

Takeaway

AI risk isn’t limited to AI companies. In venture deals and M&A transactions, AI reps and warranties are in the negotiation spotlight. On the company’s side, if you’re only turning your mind to best practices during a transaction, it’s too late. On the investor / buyer side, ensure AI risk and compliance is a core part of your due diligence checklist and rep structure.

Ink LLP is a business law firm with focused expertise in venture capital, mergers & acquisitions, and complex commercial transactions.

This information is provided for informational purposes only, is highly generalized, and is not legal advice.

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Venture Capital, M&AGeoff Dittrich