Generative AI tools have moved from experimentation to daily use across most businesses, often faster than internal policies, vendor contracts, or IP strategies have kept pace. The legal issues are not exotic, but they are easy to overlook precisely because AI tools feel like ordinary software. Below are the areas we most often see businesses address too late, after a dispute or a difficult client question has already surfaced.

Ownership of AI-Assisted Work Product

Copyright protection generally requires human authorship, which creates real uncertainty when a deliverable, whether marketing copy, code, or a design, is substantially AI-generated. Businesses that sell creative or technical work product should think through how much human authorship and editorial judgment is applied to AI output, document that process, and address ownership and AI-use disclosure expressly in client-facing agreements rather than relying on boilerplate IP assignment language written before generative AI existed.

Vendor and Customer Contract Terms

Standard software agreements were not written with AI training and inference in mind. Businesses licensing AI tools should look closely at how the vendor uses input data and outputs, including whether prompts or uploaded content are used to train underlying models, and should negotiate restrictions where that use is not acceptable. On the other side, businesses that build AI features into their own products should be equally clear with their customers about what data is used, and how.

Trademark and Brand Use in AI Outputs

Businesses are increasingly asking whether it is permissible to reference competitor or third-party brand names when using AI tools for advertising, comparison content, or search-related marketing. The nominative fair use doctrine still applies, but the scale and automation of AI-generated content raises the volume of potential exposure if brand references cross from fair, descriptive use into something that could confuse consumers about sponsorship or affiliation. A brief legal review of AI-generated marketing content before wide distribution is a low-cost safeguard.

Confidentiality and Privileged Information

Employees experimenting with consumer-facing AI tools can inadvertently expose confidential business information, trade secrets, or even privileged material by entering it into a prompt. An internal AI use policy should specify which tools are approved for business use, what categories of information may never be entered into a public tool, and how enterprise or business-tier tools with contractual confidentiality protections differ from free consumer versions.

Employment and Vendor Disclosure Obligations

A growing number of jurisdictions require disclosure when AI tools are used in hiring or employment decisions, and similar disclosure expectations are emerging in consumer-facing contexts. Businesses using AI in recruiting, performance evaluation, or customer-facing decision-making should confirm what disclosure or opt-out rights apply in the jurisdictions where they operate, since this area is changing quickly and unevenly across states.

The Takeaway

Most AI-related legal exposure comes not from using the technology, but from treating it as if existing contracts, IP practices, and confidentiality policies already account for it. A focused review of vendor agreements, client-facing IP language, and internal use policies is usually enough to close the largest gaps.

This post is intended for general informational purposes and does not constitute legal advice. Please contact Jeffrey R. Glassman, Esq. in our Corporate, IP and Technology group to discuss how these issues apply to your business.