You asked ChatGPT to draft a service agreement. It returned something that looked clean, professional, and ready to send. Then your lawyer reviewed it and flagged seven gaps—some of them expensive enough to crater a deal or expose your company to six-figure claims you thought were covered. This is not a hypothetical. LLMs are remarkably good at mimicking contract structure and producing grammatical text. They are catastrophically bad at legal precision. They invent warranty language that doesn't exist in the real contract. They restate indemnification scope in ways that actually narrow your protection. They omit clauses entirely—force majeure, tax indemnity, PDPA data processor obligations—because they weren't trained to recognize what's missing . The problem isn't that AI can't write contracts. It's that AI doesn't understand legal consequence. It optimizes for coherence, not liability. This guide walks through seven real traps lawyers catch in AI-drafted agreements, shows you what each one looks like in practice, and gives you a checklist to audit any contract—AI-drafted or human-drafted—before it becomes binding. 1. Invented warranty language that isn't actually there LLMs have seen thousands of warranty clauses in training data. When asked to draft a service agreement, they synthesize a plausible-sounding warranty section. The problem: they invent specificity that doesn't reflect what you're actually committing to. Real example: An AI drafted a SaaS agreement that promised the software would be "fit for the customer's particular purpose," "operate without material interruptions," and "meet all industry standards applicable to similar software." None of those phrases appeared in the actual service level agreement (SLA). The customer later sued on breach of the invented warranty, arguing the AI language represented a binding commitment. The company had to spend ₹80K in legal fees to argue what should have been obvious: that warranty wasn't in the negotiated contract. What to look for: Warranties that reference specific technical performance metrics not tied to a defined SLA. Promises about "industry standards" or "best practices" without citing a standard or specifying the practice. Language like "fit for purpose" without a defined purpose attached. Warranty sections that are longer or more detailed than the corresponding limitation-of-liability clause (a red flag that the AI added uninsured exposure). 2. Indemnification scope creep or restatement Indemnification clauses are where AI tends to misfire most dangerously. The AI will restate an indemnity obligation in different words, thinking it's clarifying—but those different words can actually broaden or narrow the scope in ways that flip the risk allocation. Real example: An AI drafted: "Each party indemnifies the other against any claim arising from the indemnifying party's negligence, intentional misconduct, or violation of law." The original negotiated clause said: "Each party indemnifies the other against claims arising from the indemnifying party's breach of this agreement." The AI version created new indemnity obligations not agreed to (negligence, even if not a breach; violation of law, even if unrelated to the contract). When a developer made a mistake that was negligent but didn't breach the contract, the customer demanded indemnification under the AI's language. The dispute took six months to resolve. What to look for: Indemnity language that uses words like "arising from," "related to," "caused by," or "in connection with" instead of the tighter "breach of this agreement." Indemnification that covers "negligence" or "misconduct" separately from breach. Dual-indemnity structures where the AI added a second indemnity paragraph for topics already covered in the first. Indemnity that requires the indemnified party to "mitigate" or "cooperate" without defining what that means (AI loves this vague language). 3. Force majeure clause dropped entirely Force majeure is a structural element. Either the contract has one or it doesn't. AI trained on thousands of agreements will sometimes include it; sometimes not. When it doesn't, the AI doesn't realize it's removed a critical protection—it just keeps writing as if the clause isn't necessary. Real example: An AI drafted a supply agreement for a manufacturing startup. The contract had detailed performance obligations, penalties for late delivery, and a comprehensive limitation-of-liability clause. It did not mention force majeure. When the 2020 pandemic hit and the supplier couldn't deliver, the customer sued for breach. The supplier argued that pandemic is beyond the parties' control and shouldn't create liability. The customer's lawyer pointed to the contract: no force majeure clause, therefore performance is absolute. The supplier settled for ₹35K. A 20-word force majeure clause would have prevented that entirely. What to look for: Search the contract for the word "force majeure." If it's not there, chec