Generative AI in the Workplace: Legal Considerations for Employers

Generative AI tools — systems that produce text, images, code, and other content in response to natural language prompts — have become a significant feature of the modern workplace. Employees across industries use ChatGPT, Claude, Gemini, Copilot, and similar tools to draft emails, summarize documents, write code, create presentations, research topics, and perform a wide range of other work tasks. Many of them do this without any formal employer guidance or policy. The result is that employers face legal and operational risks they have not explicitly evaluated or managed.

For employers, the challenge is not simply whether to allow or prohibit generative AI use at work — that decision, for most businesses, is already effectively made by the employee behavior that is already occurring. The more important challenge is understanding the specific legal risks that arise when employees use generative AI in the course of their employment and addressing those risks through policy, training, and governance.

Confidentiality and Trade Secret Risk

One of the most immediate legal risks of unmanaged employee generative AI use is the potential exposure of confidential business information and trade secrets. When an employee inputs a prompt into a generative AI tool, that prompt — including any information contained in it — is processed by the AI system, may be retained by the AI provider, and in many configurations may be used to train or improve the AI model. If an employee asks a generative AI tool to summarize a confidential contract negotiation, help analyze a proprietary financial model, draft a proposal based on internal pricing strategy, or review a trade secret formula, the confidential information in the prompt has been shared with a third-party system over which the employer has no control.

Under the Defend Trade Secrets Act and most state trade secret laws, a business must take reasonable measures to protect the secrecy of its trade secrets. Allowing employees to input trade secret information into public generative AI systems without restriction could undermine the business’s ability to claim trade secret protection, because the information may no longer be secret if it has been shared with an AI provider. Employers should address this risk directly in their AI use policies by prohibiting employees from inputting confidential information, trade secrets, customer data, or proprietary business information into generative AI tools that are not specifically approved for that use by the employer.

Data Privacy and Employee AI Use

If employees input personal information — customer data, employee records, patient information, financial account details — into generative AI tools in the course of their work, the employer may be violating data privacy obligations. Sharing customer personal information with a third-party AI provider without appropriate contractual protections and disclosures may constitute unauthorized sharing or a violation of applicable privacy law. If the information includes protected health information, sharing it with an AI provider without a HIPAA business associate agreement in place may be a HIPAA violation. If the information includes personal data about EU residents, sharing it with an AI provider without proper data transfer mechanisms may violate the GDPR.

Employers should evaluate whether the generative AI tools their employees are using satisfy their data protection obligations for the types of information employees are likely to input. Many enterprise versions of generative AI tools offer configurable data protection settings, including the ability to opt out of training on user inputs and to maintain data within specified geographic boundaries. Employers who want to allow employees to use generative AI tools with sensitive data should identify tools that offer appropriate contractual protections and configure them appropriately, rather than allowing unmanaged use of consumer-grade AI tools.

Intellectual Property Risks

When employees use generative AI to produce work product — code, marketing copy, reports, designs, contracts — several intellectual property issues arise. As discussed elsewhere in this blog, AI-generated content may not be eligible for copyright protection in the United States if there is insufficient human creative authorship. Work product that your employees submit as entirely their own but that was substantially generated by AI may lack the copyright protection you assume it has. If a competitor copies that AI-generated work, your ability to pursue an infringement claim may be limited.

There is also the risk that AI-generated work product infringes third-party intellectual property. Generative AI tools are trained on large quantities of copyrighted content, and their outputs can sometimes closely resemble or reproduce portions of that training data. An employee who submits AI-generated code that reproduces open-source code subject to a copyleft license may expose the employer to license violation claims. An employee who submits AI-generated marketing copy that closely resembles a competitor’s trademarked brand language may create trademark infringement risk. Employers should have quality review processes for AI-assisted work product, particularly in contexts where intellectual property originality matters.

Accuracy and Professional Standards

Generative AI systems can produce confident-sounding, detailed, and entirely incorrect information. In a professional context, an employee who relies on AI-generated information without verification and submits it as accurate creates liability for the employer. A law firm whose attorney relies on AI-generated case citations without verification — and the cases turn out not to exist — faces potential sanctions and professional discipline. A financial services firm whose analyst submits AI-generated market analysis containing factual errors faces reputational and potentially regulatory risk. A medical practice whose staff relies on AI-generated clinical information that contradicts established guidelines faces patient safety and malpractice risk.

Employers in regulated industries — healthcare, legal services, financial services, accounting — face particular exposure when employees use generative AI without appropriate oversight. Professional licensing bodies and regulators in these industries have begun to address AI use specifically, and the trend is toward requiring that AI-assisted professional work be subject to meaningful human review and that the professional using the AI remains personally responsible for the accuracy and quality of the output. Employer policies should reflect these professional standards and should require appropriate verification of AI-generated information before it is relied upon or submitted as the employer’s work product.

Discrimination and Bias Risks in AI-Assisted HR Decisions

If employees use generative AI tools to assist with HR functions — drafting job descriptions, screening resumes, preparing performance reviews, making promotion recommendations — the employer faces the discrimination and bias risks discussed in detail elsewhere in this blog. A job description drafted by generative AI may inadvertently use language that discourages applications from women or older candidates. A resume screening prompt that incorporates demographic information may produce biased results. A performance review template generated by AI may reflect implicit biases embedded in the AI’s training data.

Employers should treat AI-assisted HR functions with the same scrutiny they apply to dedicated AI hiring tools, because the legal standard is the same: the employer is responsible for the discriminatory effects of decisions made with AI assistance regardless of whether the AI was a purpose-built HR tool or a general-purpose generative AI. HR professionals should be trained to review AI-generated HR content critically for potential bias and to ensure that any AI-assisted selection or evaluation process complies with applicable anti-discrimination law.

Elements of an Effective Workplace AI Policy

Every employer should have a written policy governing employee use of generative AI tools in the workplace. The policy does not need to be prohibitive — in fact, overly restrictive AI policies that employees ignore are worse than well-calibrated policies that employees actually follow. The goal is a policy that enables productive AI use while managing the specific risks the business faces.

An effective workplace AI policy should identify which generative AI tools are approved for use and in what contexts, which tools are prohibited (particularly consumer-grade tools for tasks involving confidential information), the types of information that may never be input into any AI tool without specific authorization, the requirement that AI-generated work product be reviewed and verified before submission or use, the employer’s policy on disclosing AI assistance to clients, customers, or other parties when relevant, and the employee’s responsibility for the accuracy and compliance of any work product they submit, regardless of whether AI was used in its preparation.

The policy should also be accompanied by training that helps employees understand not just what the policy says but why — the specific risks that the policy is designed to manage. Employees who understand the reasons behind an AI use policy are more likely to follow its spirit when they encounter situations the policy does not specifically address, which is inevitable as AI tools evolve faster than any written policy can track.

AI Governance as an Ongoing Practice

A one-time AI policy is not sufficient. The generative AI landscape is changing rapidly: new tools are released constantly, existing tools change their capabilities and data practices, and the legal and regulatory framework continues to develop. Employers should treat AI governance as an ongoing practice rather than a compliance exercise that is checked once and forgotten. This means reviewing and updating the AI use policy at least annually, monitoring regulatory developments and legal proceedings that may affect AI use in the workplace, evaluating new AI tools before approving them for employee use, and creating a mechanism for employees to raise questions or concerns about specific AI use cases that the policy does not clearly address.

The employers who manage generative AI in the workplace most effectively are those who approach it as a governance challenge rather than simply a technology decision. They take advantage of the productivity benefits that generative AI offers while implementing the policy, training, and oversight structures that manage the legal and operational risks. In a competitive landscape where AI tools are becoming ubiquitous, the businesses that use them well — productively and responsibly — will have a meaningful advantage over those who either ignore AI entirely or allow its use without any structure or accountability.