From Storylines to Strategies: Addressing AI-Amplified Trade Secret Leak Threats in Entertainment

• Generative AI tools create significant new risks for the inadvertent or intentional disclosure of entertainment trade secrets, from unreleased scripts and storylines to confidential business strategies.
• Traditional safeguards like confidentiality agreements, access controls, and employee training should be updated to address AI-specific risks, including data ingestion by third-party platforms and the portability of AI-assisted knowledge.
• Employers should implement comprehensive AI governance frameworks, particularly where noncompete restrictions are unavailable or limited, as in California.

Generative artificial intelligence (GAI) presents a new and evolvinged on confidentiality and secrecy to preserve the value of its creative assets

Pre-release films, television series, music albums, video games, and streaming initiatives often depend on maintaining secrecy until launch. A leaked plot twist, early script draft posted online, or a prematurely revealed casting decision can diminish audience anticipation and undermine a project’s market performance. As employees and contractors increasingly integrate AI tools into their daily workflows, entertainment employers face escalating challenges in preventing the inadvertent disclosure of confidential information.

How Does AI Create New Exposure?

GAI platforms generally function by ingesting user-submitted content and processing it to generate responsive output. This can create substantial confidentiality risks when a worker submits proprietary or sensitive material to a third-party AI tool. Depending on the platform’s terms of service, submitted content may be retained, used for model training, or stored in ways that compromise confidentiality of the material and the employer’s control.

In a production environment, these risks arise in a variety of practical, everyday activities. Consider:

• A screenwriter pastes portions of an unreleased script into a chatbot interface, seeking suggestions to sharpen dialogue or restructure a scene.
   
• A production coordinator asks a GAI tool to summarize or reorganize a confidential shooting schedule, exposing location details, talent availability, and budget information.
   
• A visual effects artist submits proprietary code to an AI debugging assistant, potentially disclosing techniques that give the studio a competitive advantage.
   
• An HR manager uses an AI tool to rewrite or reorganize a confidential cast or crew investigation report, transmitting sensitive personnel information and legal conclusions to an external platform.

Each of these scenarios involves a well-intentioned worker seeking greater efficiency, but doing so may result in the disclosure of material that qualifies as a trade secret under federal and state law.

Beyond these unintentional disclosures, some employees may deliberately exploit AI tools to extract, compile, or retain proprietary information for personal advantage or future employment elsewhere.

Worker Departing?

GAI enables a user to simply carry an organization’s institutional knowledge “out the door.” Traditional methods of misappropriation, such as copying files to a personal device or emailing documents to a private account, may soon seem comparatively unsophisticated.

Today, departing executives, creative professionals, and other users can use GAI to reorganize months of confidential meeting notes, project briefs, and strategic documents into portable summaries. An employee can build a personal AI-driven knowledge base drawn from proprietary company materials, capturing not just discrete documents but patterns, strategies, and frameworks that constitute the company’s valuable institutional intelligence. Prompt histories and AI-generated outputs may serve as a reconstructed version of the employer’s confidential information, repackaged in a form that is difficult to trace or recover.

These concerns are particularly pronounced in jurisdictions where noncompete agreements are unenforceable or significantly restricted. In California, for example, employers generally may not prevent a former employee from working for a competitor. Therefore, trade secret protection often becomes the primary legal means for safeguarding the company’s proprietary information. The employer must demonstrate it took reasonable measures to maintain secrecy. If an employer has not adapted its confidentiality safeguards to address how GAI tools operate, AI-facilitated disclosure of confidential information can undercut protective measures upon which the employer relies.

How to Build an AI-Aware Protection Framework?

Employers should not rely exclusively on their existing confidentiality infrastructure. GAI’s capacity to facilitate easy data submission and sharing, obscure third-party processing, and highly portable prompt-generated output call for updated and layered protections. Accordingly, employers should take reasonable steps to safeguard their information and be better positioned to enforce trade secret rights if a dispute arises.

• Establishing approved-tool policies and procedures that identify vetted AI platforms with acceptable data-handling terms and prohibit the use of unapproved alternatives;
   
• Updating confidentiality and nondisclosure agreements to expressly address the submission of protected information to AI platforms, whether internal or third-party;
   
• Implementing access controls that restrict which employees and contractors may use GAI tools and define which categories of information may never be submitted to any AI system;
   
• Conducting targeted training for employees and contractors that identifies common AI-related disclosure scenarios and clarifies expectations;
   
• Performing vendor diligence on AI service providers, focusing on data retention, model training practices, and contractual confidentiality commitments;
   
• Developing incident-response procedures specifically tailored to unauthorized AI disclosures, including prompt forensic investigation and notification protocols;
   
• Strengthening offboarding procedures to address AI-related retention risks, including review of prompt histories, personal AI accounts, and AI-generated work product; and
   
• Adopting a comprehensive AI governance policy that integrates trade secret protection into the organization’s broader framework for responsible AI use.

Looking Ahead

The rapid adoption of GAI across the entertainment industry shows no sign of slowing. As these tools become more capable and more deeply embedded in creative and operational workflows, the avenues for trade secret exposure will continue to multiply. Entertainment employers that proactively modernize their confidentiality frameworks through updated agreements, meaningful training, thoughtful technology governance, and robust departure protocols will be best positioned to protect their most valuable assets in an increasingly complex and evolving landscape.

Please contact your Jackson Lewis attorney for support regarding GAI or trade secret issues in your workplace. 

Focused on employment and labor law since 1958, Jackson Lewis P.C.’s 1,100+ attorneys located in major cities nationwide consistently identify and respond to new ways workplace law intersects business. We help employers develop proactive strategies, strong policies and business-oriented solutions to cultivate high-functioning workforces that are engaged and stable, and share our clients’ goals to emphasize belonging and respect for the contributions of every employee. For more information, visit https://www.jacksonlewis.com.