AI Liability, Contracts & Risk Allocation
AI risk is ultimately allocated in contracts and tested in disputes. We draft and negotiate AI-specific MSAs, SLAs, and statements of work — including performance, hallucination, and misuse warranties — and design indemnities, limitation-of-liability structures, and insurance alignment. When claims arrive, the same team defends product liability, professional negligence, and commercial disputes.
Who this is for
AI vendors selling into enterprises, enterprises procuring AI, professional services firms deploying AI tools, and insurers/brokers needing coverage-aware contract language.
What you get
- AI MSA, SLA, DPA, and AUP templates with hallucination and output disclaimers
- Indemnity, warranty, and liability cap structures matched to real risk
- Customer paper negotiation and redline support
- Model output, benchmark, and uptime representation drafting
- Insurance coordination for cyber, tech E&O, and product exposures
- Dispute defense when AI outputs or decisions are challenged
Frequently asked questions
Can we warrant that our model will not hallucinate?
A full accuracy warranty is rarely insurable or wise. Prefer bounded representations (defined eval thresholds, human-review requirements, fitness limitations) with clear exclusions for misuse and out-of-scope use, paired with remedies like credits or re-performance rather than unlimited liability.
How should liability be capped for AI services?
Most commonly at fees paid over a trailing 12 months, with super-caps or carve-outs only where the customer demands them for specific risks (data breach, IP infringement, confidentiality). The key is aligning the cap with insurance capacity and deal value.
Do we need a separate AI addendum to our MSA?
Usually yes. Standard IT MSAs do not address model training on customer data, output ownership, eval evidence, human oversight expectations, or regulatory cooperation. A focused AI addendum closes those gaps cleanly.