Generative AI and Trade Secret Protection for Businesses

As businesses continue adopting artificial intelligence tools, protecting confidential information requires a proactive approach. Traditional trade secret protection methods remain important, but companies must now consider how AI systems affect information security, employee behavior, and data management.

Under U.S. trade secret law, companies generally must take reasonable measures to maintain secrecy. A business that allows employees to freely upload confidential information into external AI systems without restrictions may create arguments that the information was not adequately protected.

For this reason, companies should treat generative AI adoption as both a technology issue and a legal compliance issue.

A strong AI governance strategy should begin with identifying what information qualifies as confidential. Not all company information receives trade secret protection. Businesses should determine which information provides competitive value and should receive additional safeguards.

For example, a software company may consider its source code, product roadmap, and proprietary algorithms confidential. A manufacturing company may need to protect production methods, formulas, engineering designs, and supplier information. A professional services company may need to protect client data, pricing strategies, and internal processes.

Once sensitive information is identified, companies can create appropriate restrictions around how employees interact with AI tools.

Creating Internal Generative AI Policies

One of the most important steps businesses can take is creating a clear generative AI usage policy.

Many employees are already using AI tools to improve productivity, sometimes without realizing the legal consequences of sharing company information. A written policy provides guidance and helps establish expectations regarding acceptable AI use.

A well-designed AI policy should explain how employees can use AI tools while protecting confidential information. It should address whether employees may use public AI platforms, what types of information cannot be entered into AI systems, and when approval from management or legal teams is required.

For example, employees may be permitted to use AI for general tasks such as brainstorming, drafting non-confidential communications, or improving writing. However, they may be prohibited from entering confidential contracts, customer records, unreleased product information, or proprietary business data into external AI systems.

Clear policies also help businesses demonstrate that they took reasonable steps to protect trade secrets. If a dispute arises, courts may examine whether the company had procedures in place to prevent unauthorized disclosure.

Employee Training and Awareness Are Critical

Creating an AI policy is only effective if employees understand and follow it.

Many trade secret risks occur because employees do not recognize that certain actions may expose confidential information. An employee may believe that using an AI assistant to summarize an internal document is harmless, even though the document contains proprietary information.

Regular training can help employees understand the risks associated with AI tools. Businesses should explain why confidential information requires protection, how AI systems handle information, and what steps employees should take before using AI applications.

Training should also emphasize that artificial intelligence should support employee work rather than replace careful judgment. AI-generated content may contain errors, security concerns, or unauthorized disclosures if used improperly.

A company culture that encourages responsible AI use can significantly reduce the risk of accidental trade secret exposure.

Protecting Trade Secrets Through AI Vendor Agreements

Businesses should carefully review agreements before adopting third-party AI platforms.

Many companies rely on external AI providers rather than developing their own artificial intelligence systems. While these tools can increase efficiency, they may also create uncertainty regarding data ownership, storage, and confidentiality.

Before entering into an AI service agreement, companies should examine how the provider handles customer information and whether the contract includes appropriate protections.

Important considerations include whether the provider can use customer data to improve AI models, how long information is retained, what security measures are used, and what happens if a data breach occurs.

A company should avoid assuming that an AI provider automatically protects confidential information simply because the platform is widely used. Businesses must evaluate whether the technology aligns with their legal obligations and internal security standards.

The National Institute of Standards and Technology (NIST) provides guidance for managing artificial intelligence risks through its AI Risk Management Framework, which businesses can use when evaluating AI-related risks.

Generative AI and Confidentiality Agreements

Confidentiality agreements have long been an important tool for protecting trade secrets. However, businesses may need to update these agreements to address artificial intelligence.

Traditional confidentiality agreements often focus on preventing employees from sharing information with competitors or unauthorized individuals. Modern agreements may also need to address how employees use AI tools.

For example, companies may include provisions explaining that confidential information cannot be entered into unauthorized AI platforms. They may also clarify that employees must follow company-approved procedures when using artificial intelligence for work-related tasks.

These agreements can strengthen a company’s argument that it took reasonable steps to protect confidential information.

However, confidentiality agreements alone are not enough. Courts generally look at the overall efforts a business makes to maintain secrecy, including technical safeguards, employee training, access controls, and organizational policies.

Risks of Losing Trade Secret Protection Through AI Use

One of the biggest concerns surrounding generative AI is whether improper use could weaken trade secret protection.

Trade secrets are valuable because they are not publicly available. If a company fails to protect confidential information, it may lose the ability to claim legal protection.

For example, if employees regularly upload proprietary business information into publicly available AI tools without restrictions, a company could face challenges proving that it treated the information as confidential.

A competitor accused of using similar information might argue that the information was no longer secret because the company failed to maintain adequate safeguards.

This does not mean businesses cannot use generative AI. Instead, it means companies must integrate AI into their operations responsibly.

A business that creates strong security procedures, limits access, trains employees, and monitors AI usage is better positioned to protect its intellectual property.

Generative AI and Trade Secret Litigation

As AI adoption grows, disputes involving artificial intelligence and trade secrets are likely to increase.

Trade secret litigation traditionally involves allegations that someone improperly acquired, disclosed, or used confidential business information. Generative AI introduces new questions about how information moves between employees, companies, and technology providers.

Future disputes may involve situations where:

• An employee uploads confidential company information into an AI platform before leaving a company.
• A competitor uses AI to recreate a business process based on improperly obtained information.
• A company claims an AI provider improperly used confidential data.
• Employees use AI-generated materials that contain protected company information.

Courts may need to determine how existing trade secret principles apply to new AI-related situations.

Because AI technology continues developing rapidly, businesses should prepare now rather than wait until a dispute occurs.

Protecting Intellectual Property in the AI Era

Trade secrets are only one part of a company’s intellectual property strategy. Generative AI also creates challenges involving copyrights, patents, and trademarks.

For example, businesses using AI-generated content may need to consider whether they own the resulting material and whether third-party intellectual property rights are involved.

Companies developing AI technologies may also need to protect proprietary models, training methods, software systems, and technical processes.

A comprehensive intellectual property strategy should consider how AI affects every area of business innovation.

Related topics businesses should evaluate include:

• Ownership of AI-generated inventions
• Copyright protection for AI-assisted works
• Trademark risks involving AI-generated branding
• Protection of proprietary AI systems

Best Practices for Businesses Using Generative AI

Businesses do not need to avoid artificial intelligence to protect trade secrets. Instead, they should create responsible systems that allow innovation while reducing legal risks.

Companies should begin by understanding what confidential information they have and where that information is stored. They should evaluate which employees need access to sensitive data and establish appropriate security controls.

AI tools should be reviewed before implementation, especially when they involve confidential business information. Companies should understand how providers handle user data and whether enterprise protections are available.

Employees should receive clear instructions about acceptable AI use. Regular training and updated policies can help prevent accidental disclosures.

Businesses should also monitor changes in AI technology and legal developments. Regulations and court decisions involving artificial intelligence are continuing to evolve, meaning companies should regularly review their practices.

The Future of Generative AI and Trade Secret Protection

Artificial intelligence will continue changing how businesses operate. Companies that successfully integrate AI will likely gain advantages in productivity, innovation, and efficiency.

However, the businesses that benefit most will be those that recognize AI as both an opportunity and a legal responsibility.

Trade secret protection has always required companies to balance accessibility with confidentiality. Generative AI adds another layer to that challenge because information can now be processed, transformed, and shared through systems that employees may not fully understand.

Future laws and regulations may provide additional guidance regarding AI data practices, but businesses should not wait for new rules before improving their internal protections.

Companies that establish responsible AI policies today will be better prepared for future legal challenges.

Conclusion

Generative AI is transforming the business landscape, but it also creates new challenges for protecting confidential information. Trade secrets remain one of the most valuable assets a company can own, and businesses must adapt their protection strategies to address modern technology risks.

The relationship between generative AI and trade secret protection requires careful planning. Companies should evaluate AI tools, create clear employee policies, strengthen cybersecurity practices, and ensure that confidential information remains protected.

While artificial intelligence can provide significant benefits, businesses must use it responsibly. Protecting trade secrets in the AI era is not about limiting innovation. It is about creating safeguards that allow companies to embrace new technology without sacrificing their most valuable information.

As AI continues evolving, businesses that combine technological innovation with strong legal protections will be better positioned to compete in the future.