Artificial intelligence is no longer coming. It is already embedded in your product roadmap, your vendor stack, and your board’s expectations. For startup general counsel, that means one thing: The pressure to move fast without breaking the company is real and it is yours to manage.
Navigating AI product integration requires more than a passing familiarity with emerging regulations. It calls for a proactive legal strategy that keeps pace with your engineering team, satisfies investors, and holds up under regulatory scrutiny.
Before your next sprint review, here are five things startup counsel should keep in mind when integrating AI into your products.
1. Intellectual Property Rights
To help protect your organization’s intellectual property rights, it is important to remember that under the U.S. Copyright Office’s current position and guidance, AI-generated outputs (text, images, code) may not be protected under copyright law unless there is sufficient human-authored creative expression, so there may be risks associated with claiming ownership of any AI outputs.
2. Model Transparency and Explainability
State laws like those in California will require organizations to provide disclosures when customers interact with AI systems or AI companions, and many states have proposed similar regulations. If your organization is implementing an automated decision-making system, particularly one that produces a legal or similarly significant effect, ensure that you are complying with applicable regulations. It may be beneficial to run regular checks for bias and disparate impact, documenting such findings and integrating them as part of your AI governance framework.
Additionally, some states have imposed transparency regulations regarding GenAI models. For example, the California AI Transparency Act will require disclosures around AI-generated content (effective August 2, 2026, as amended by California AB 853), and California AB 2013 (effective January 1, 2026) addresses training data transparency.
3. Model Outputs and Acceptable Uses
In addition to model explainability and data governance, it is important to build in technical guardrails to reduce risks from hallucinations, misinformation, or harmful or offensive outputs.
From a consumer standpoint, terms of service and acceptable use policies may be used to clearly delineate prohibited practices and require compliance with applicable laws. It is important to understand what content is prohibited and what liabilities would attach for violations of regulations such as Tennessee’s ELVIS Act (pertaining to a person’s name, image, or voice), the Take it Down Act (pertaining to nonconsensual intimate deepfakes), or California’s SB 243 (pertaining to chatbots operating as “companions”). Also, providing clear disclosures and indicators that the model outputs are AI-generated may help protect both the consumer and your organization.
4. AI Leadership and Internal Policies
Consider establishing a cross-departmental AI governance team that includes members of the legal, HR, product/engineering, and IT/information security departments. Assembling stakeholders across the organization may help to ensure that current and planned AI use cases are identified and properly assessed for risks.
Having dedicated personnel to audit and evaluate the organization’s AI use cases may also help your organization stay ahead of emerging risks, set clear policies, and keep ethical and regulatory considerations front and center as you scale your AI initiatives.
Consider implementing an AI governance policy that sets out guidelines for how AI should be used by the organization and that explicitly highlights security measures and confidentiality obligations relating to the use of AI.
While consumer-facing AI is often the focus, it is equally important to manage and safeguard internal uses of AI tools. Doing so may help demonstrate to stakeholders and auditors that AI is being used responsibly.
5. Stay Informed on Upcoming Regulations
AI laws are evolving fast, especially in the European Union and some U.S. states. While there is not yet a uniform federal law on AI governance, states are actively working to propose and enact regulations that directly impact businesses.
Organizations should align their product features and roadmaps to relevant obligations, keep privacy notices up to date, and watch for new disclosure or labeling requirements.
Stay informed on proposed and upcoming AI-related laws and take note of the applicable jurisdictions. Several U.S. states have passed AI governance laws that are either already in effect or may go into effect at various points in 2026.