AI and software-as-a-service contracts often present a mismatch between a simple subscription price and substantial operational exposure. The platform may process confidential records, generate business-critical outputs, integrate with customer systems, or become difficult to replace. A useful legal review begins with the actual workflow, not the vendor’s description of its technology.
Identify every category of data
Separate customer-uploaded documents, prompts, generated outputs, account metadata, usage logs, derived analytics, and vendor-owned materials. An agreement may say the customer owns its data while giving the vendor broad rights to use that data for analytics or product development. Ownership is not the same as a restriction on use.
Determine whether the vendor may use inputs or outputs to train models, whether opt-outs are effective, and whether subprocessors receive the same restrictions. Examine retention and deletion rules, including backups and legal holds. Contract promises should match the platform’s actual settings and technical architecture.
Protect confidential and regulated information
Businesses may upload contracts, personnel files, patient information, student records, source code, or financial forecasts. The agreement should describe authorized processing purposes, access controls, confidentiality, incident notification, and security responsibilities. Sensitive data may trigger sector-specific requirements.
For healthcare use, assess whether the vendor is a business associate and whether the HIPAA rules require an agreement under 45 C.F.R. Part 164. Educational deployments may require analysis of FERPA, state student privacy laws, and school contracts. No single contractual claim of “compliance” resolves every customer’s obligations.
Decide who is accountable for AI output
Generative tools can produce inaccurate statements, unsupported citations, flawed summaries, or inappropriate recommendations. A vendor may advertise efficiency while disclaiming responsibility for output accuracy. The customer should identify whether the product is intended for low-risk drafting or consequential decisions and negotiate warranties and controls accordingly.
Human oversight, testing, escalation rules, and prohibited uses may be as important as contract wording. The NIST AI Risk Management Framework provides a voluntary risk-management reference, not a universal safe harbor.
Examine ownership and licensing
Clarify rights in customer inputs, outputs, customized configurations, integrations, and vendor software. A customer may need a perpetual right to use exported materials after the subscription ends. Conversely, a vendor may reasonably retain its preexisting tools and generalized know-how. The contract should avoid language that inadvertently transfers a customer’s proprietary materials or restricts ordinary post-termination operations.
Test the intellectual-property indemnity
Some AI vendors offer limited defense against third-party infringement claims. Review exclusions for prompts, customer modifications, combinations with third-party software, prohibited uses, and continued use after a vendor warning. Identify who controls the defense, whether settlements can impose obligations on the customer, and whether the indemnity falls within a general liability cap.
A broad headline promise can be narrowed substantially by exclusions. The relevant question is whether protection covers the way the business will actually use the system.
Match liability caps to foreseeable harm
A cap equal to twelve months of subscription fees may be proportionate for a minor productivity tool and inadequate for a system containing sensitive records or supporting core operations. Consider differentiated caps or exceptions for specified security, confidentiality, intellectual-property, or intentional misconduct claims. Review insurance requirements and whether the vendor can satisfy a significant obligation.
Make termination operationally possible
Identify export formats, migration support, transition periods, deletion certification, subcontractor cooperation, and post-termination access. For an AI platform embedded in business workflows, continuity may depend on transferring prompts, templates, audit histories, and integrations as well as raw data. A termination right is not useful if exercising it prevents the business from functioning.
Also examine unilateral changes to acceptable-use policies, models, pricing, service levels, and functionality. If the vendor can materially change the product, determine whether the customer receives notice and a meaningful exit option.
Align contract terms with internal governance
Even a carefully negotiated agreement cannot replace employee training, authorized-use rules, review of consequential outputs, and incident-response procedures. The business should maintain an inventory of deployed tools, assign responsibility for vendor monitoring, and periodically confirm that actual practices remain within the negotiated data permissions.
Contract review is ultimately an exercise in understanding who controls information, who bears the cost of failure, and whether the organization can leave without disproportionate harm.
Review an AI or software agreement: BOLO Health Law advises businesses on technology contracts and commercial data risks. See AI, Technology, EdTech & Data Privacy Contracts or request a matter review.
Further references: FTC Business Guidance; NIST AI RMF; U.S. Department of Education Student Privacy.
Related BOLO analysis: For related development issues, read custom software ownership, deliverables, and integration terms.
General legal information, not legal advice. Outcomes depend on the facts and governing law. An initial inquiry does not establish an attorney-client relationship. Do not send confidential, privileged, or protected health information through an initial web form.