Every week, in-house lawyers are bombarded with contracts for AI tools promising efficiency and time savings. But a deeper examination of these terms and conditions reveals potentially costly traps.

The allure of AI tools is undeniable as vendors aggressively market to various teams within organizations. These contracts, often adorned with standard terms, are quickly clicked through by many, but in-house lawyers must scrutinize every detail.

Take, for instance, a recent contract I reviewed for an AI-powered content platform. The initial offer seemed straightforward with modest fees and polished sales pitches. However, the reality hidden within the standard agreement was far from simple.

Upon closer inspection, four major issues emerged, none related to the usual suspects of cybersecurity or data breaches, but all concerning data control. The vendor claimed co-ownership of any content created by the AI using the client's data, allowing them free reign to use this content, even potentially sharing it with competitors, without needing consent.

Moreover, the agreement granted the vendor perpetual, irrevocable access to the client's data under the guise of "Aggregated Statistics," a term so broadly defined that it offered no real protection to the data's original owners. Once the data was entered into the system, it was essentially out of the client’s control.

The contract also allowed the vendor to unilaterally suspend the service for various reasons without consequence, leaving the client without similar termination rights. This meant that in the event of an indefinite suspension, the client would be left without recourse, continuing to pay for a non-functioning service.

Additionally, the agreement included a branded microsite where content would be published. However, it failed to clarify ownership of the domain or the fate of the content post-contract, potentially leaving the client paying for a site they neither owned nor controlled.

These critical issues often do not appear on standard contract review checklists. While such checklists might flag important clauses like limitation of liability or indemnification, they miss out on the nuanced risks posed by data control terms.

This pattern is common across AI vendor agreements: the technology might be new, but the contracts follow an old playbook that favors vendors, wrapping significant risks in familiar legalese.

For in-house lawyers, the takeaway is clear: scrutinize every aspect of IP ownership, track how data is handled throughout the contract, seek symmetry in termination rights, and explicitly define ownership of any deliverables. AI tools will continue to proliferate, and while the technology advances, the contracts must be approached with a critical eye to protect the interests of the client.

In short, it's not just about understanding the technology but understanding the legal bindings that come with it. Before agreeing to any terms, it's crucial to dig deep and push back against vendor-favoring conditions. This is where the true battle for control and security is fought—in the fine print.