Hidden Legal Risks of Using AI for Legal Work (Part I: Contract Drafting)

AI tools are increasingly used to draft contracts and to revise contract language. They can be useful for first drafts and summaries, but they can also introduce issues that create real legal and commercial exposure that companies need to be aware of, especially when their teams are moving fast.  This is Part I of a two-part series on the legal risks of using AI for legal work: Part I focuses on contract drafting risks, and Part II will focus on the risks of using AI for legal guidance and decision-making.

Below are five common patterns we tend to see in AI-generated contract language, and what to watch for:

1. Incorrect or Inconsistent Definitions

AI drafts often forget to define key terms, or define them incorrectly based on the context. Crisp definitions are critical in contracts and a small definition problem can ripple through multiple sections and impact key obligations.

Example: An AI-generated services agreement defined “Services” to include implementation and ongoing support, but later described “Support Services” as a separate add-on. The fees section tied pricing to “Services,” creating ambiguity about whether support was included in the base price and whether service levels applied to support.

2. Clauses That Look Neutral but Are One-Sided

Even when you instruct AI to draft provisions in your “favor,” AI will often draft provisions that are more favorable to the counter-party even though upon first glance they may seem standard or mutual until you pay attention to details such as carve-outs and cross-references, especially in limitation of liability, indemnities, and termination.

Example: An AI draft included a “mutual” liability cap (fees paid in the last 12 months), but carved out the counter-party’s preferred claims from the cap (including indemnity and “any violation of law”) while leaving the client’s most likely claims capped. On paper it looked balanced; in practice it shifted meaningful risk in one direction.

3. Over-reliance on Generic “Standard” Language

AI drafts contracts by pulling language from generalized patterns. That approach can lead to contracts missing key provisions, or the inclusion of terms that are simply inapplicable or inappropriate to the particular industry or type of relationship/transaction at issue.

Example: An AI-generated SaaS agreement contained generic confidentiality terms but omitted key data terms the relationship required, including breach notification timing, sub-processors, and a workable security framework. Those gaps mattered far more than the “standard” boilerplate confidentiality language it included.

4. Misalignment With Business Operations

AI doesn’t know how your team actually delivers products or services, recognizes revenue, invoices, or handles operational issues. This leads to contracts that do not reflect your actual practices and workflows, which in turn can create friction between the parties and lead to inadvertent contract breaches.

Example: An AI-generated implementation agreement promised a fixed go-live date with automatic service credits for any delay. But the timeline assumed the customer would deliver data, access, and approvals on day one—things the vendor couldn’t control. When the customer missed inputs, the vendor still looked “late” under the contract, handing the customer leverage to demand credits, concessions, or termination.

5. Failure to Identify the True Risk Driver

AI can focus on something adjacent (or lower impact) and miss the clause that actually drives leverage and loss.  It also tends to treat clauses in isolation, instead of reading how provisions interact - especially termination, payment, renewals, minimum commitments, remedies, and transition obligations.  A more risk-focused review would spot the “stack” of interacting terms and push for basics like a wind-down/transition period, clear refund/fee treatment on early termination, and continuity obligations for critical services.

Example: In a commercial agreement, the AI flagged notice wording and governing law, but didn’t identify the core business risk: short-notice termination for convenience combined with non-cancellable fees and no transition/wind-down obligations. That interaction can turn a routine “termination right” into stranded cost and business interruption - precisely when you have the least leverage.

Practical Takeaways

AI can be a helpful starting point, but it is not a substitute for context-specific legal judgment, negotiation strategy, and deal structuring. In our experience, the biggest problems are not just drafting errors. They are structural, including contracts that are built on the wrong framework for the relationship, include irrelevant provisions, or omit clauses that are essential to protect the client.

If you use AI in your contracting workflow, treat the output as a draft and pressure-test it for: 

• whether the agreement matches the actual relationship (vendor vs. partner vs. reseller vs. contractor, and who is taking which risks), 

• whether key clauses are missing or off-base for the deal (for example, IP ownership and license scope, data/security terms, acceptance criteria, change control, termination and transition, insurance, and dispute resolution), 

• whether definitions, cross-references, and remedies align across the document, and 

• whether the liability structure reflects the real exposure (caps, carve-outs, indemnities, and any uncapped obligations).

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Our team helps companies triage AI-generated drafts quickly, identify what needs to be rebuilt versus revised, and deliver business-practical redlines and negotiation guidance tailored to the transaction. Reach out to us for a tailored legal review and actionable guidance.

About the AuthorJacqueline Piscitello is a Founding Partner of ExecutiveGC, LLP, where she and her team provide practical, business-focused legal counsel to growing companies. Contact Jacqueline to discuss how ExecutiveGC can help protect your business.

This article is for general informational purposes and does not constitute legal advice.