Advanced or deep learning AI, particularly generative AI and large language models (LLMs), is revolutionizing the video game industry. These tools accelerate development, enrich gameplay, and enable personalized, dynamic experiences. AI has grown from rudimentary pathfinding and procedural generation to systems capable of nuanced NPC behavior and real-time narrative adaptation, creating “Living Games”. Yet, with these innovations come legal, ethical, reputational and business risks that many studios are unprepared to manage.

Unlike other creative industries, game development operates within a uniquely complex legal and regulatory environment. Studios must comply with platform terms, publisher agreements, international privacy and consumer and child protection laws, age-rating requirements, and an evolving patchwork of AI-specific regulations, all while managing teams and serving players across multiple jurisdictions.

This complexity demands more than ad-hoc approaches to AI adoption. It requires comprehensive AI governance frameworks that protect studios from legal exposure while enabling creative innovation.

The Unique Legal Landscape

A Multi-Jurisdictional Compliance Quagmire. Regulation impacting the video game industry has grown increasingly complex in recent years, and the introduction of deep learning AI has raised the stakes even higher.

In the EU, the AI Act, effective from 1 August 2024, introduces a risk based framework under which unacceptable risk AI is banned, high risk AI is subject to stringent transparency, quality, and human oversight obligations and requires conformity assessments, and limited risk AI demands transparency such as disclosure that users are interacting with AI. Minimal risk AI, including most game AI, remains unregulated for now. However, general purpose AI models carry added transparency and documentation obligations. Game developers may be classified as deployers, especially when using AI tools internally or within the EU market. Even minimal risk AI may require user notification or transparency measures.

In the U.S., Colorado’s AI Act mandates disclosures for consumer-facing AI and algorithmic impact assessments for the use of AI in connection with consequential decisions (such as hiring team members). Additionally, the use of AI to make employment decisions or other decisions that “produce legal or significant effects” is regulated under the comprehensive privacy laws in many US states and some local laws like New York City Local Law 144, and the GDPR grants EU data subjects the right to explanations of automated decision making. Meanwhile, compliance obligations under child privacy and online safety laws, such as COPPA, the UK’s Age Appropriate Design Code, the Online Safety Act, and similar regulations, become even more significant when AI features are incorporated into games that are directed to or accessible by children.

Further complications arise around biometric data. For example, AI tools analyzing player behavior or physiological responses, such as eye tracking, facial expression input, keystroke dynamics, anti-cheat monitoring or QA research, may trigger compliance obligations under biometric privacy laws in states like Texas, Illinois, and Washington, as well as under comprehensive state privacy laws that treat biometric data as sensitive data. These and other consumer protection regulations overlap to create a compliance matrix many studios struggle to comply with, especially without specialized legal guidance.

Intellectual Property Considerations. In addition to regulatory compliance issues, using deep learning AI in game development brings a new dimension to traditional intellectual property concerns. If training datasets include copyrighted game assets, music, or character designs without proper licensing, studios could face infringement claims. The risk grows if generated assets resemble protected works. Moreover, the legal status of AI generated code and assets remains unsettled. While the U.S. Copyright Office has signaled that works created with meaningful human involvement may qualify for protection, the threshold for human involvement remains undefined, creating serious ambiguity for studios developing high value franchises.

Publicity Rights and Performers’ Protections. Publicity rights issues may also be raised by the use of AI in games. For example, the new SAG-AFTRA interactive media agreement, ratified on July 9^th of this year, establishes groundbreaking protections for digital replicas and the use of AI in connection with the use of union talent voices and likenesses in games. Studios must now navigate new consent and disclosure requirements, compensation structures, and usage limitations when deploying AI-generated digital replicas of union performers in their games.

Outside the union context, studios using AI tools to create synthesized voices or character visuals risk publicity rights claims, particularly if the tools were trained on unauthorized voices or likenesses or if the outputs closely resemble real individuals. Similar issues are already playing out in real time, as seen in Lehrman v. Lovo, Inc. in the Southern District of New York and Vacker v. Eleven Labs in the District of Delaware, which settled just this week.

NPCs and Chatbots Going Rouge. There are also inherent risks whenever consumers interact with AI systems because these systems are both unpredictable and fully capable of doing or “saying” things that can be harmful to players and studio brands. Take Fortnite’s potty-mouthed Darth Vader incident for example or the CharacterAI chatbot, which is at the center of the Garcia v. Character Technologies lawsuit in the Middle District of Florida, alleging the bot contributed to the suicide of a 14-year-old boy.

Data Confidentiality in Collaborative AI Workflows. Incorporating AI into workflows can also put trade secrets and other confidential information at risk if proper safeguards are not in place. Game development typically involves multiple external partners, including publishers, platform holders, marketing agencies, outsourcing studios and middleware vendors, under NDA and other contractual confidentiality obligations. When development teams input confidential or proprietary game scripts, unreleased artwork, player analytics, or competitive intelligence into third-party AI systems, they risk compromising confidentiality and breaching their agreements. Moreover, the interconnected nature of game development means a single confidentiality breach can trigger cascading legal consequences across multiple business relationships.

Meeting Recording and Surveillance Risks. Using AI-powered transcription and meeting analysis tools can create liability risks for studios if not implemented carefully. These tools have become common in remote game development workflows. However, unauthorized recording can violate notice and consent requirements under federal wiretap laws and state privacy statutes like the California Invasion of Privacy Act. Furthermore, game development meetings often involve discussions about unreleased content and other confidential matters. Under certain circumstances recording may compromise attorney-client privilege or create discoverable evidence in future litigation. All notetaking tools should be thoroughly vetted to ensure that meeting discussions remain confidential.

Platform Policies and Distribution Risks. Additionally, major gaming platforms such as Steam, Apple, and Google, are developing specific policies around AI-generated content with some platforms requiring the disclosure of AI use in game assets, and others implementing quality standards for AI-generated content. Failure to comply with platform policies can result in game rejection, removal from storefronts, or account suspension which could be potentially devastating for studios dependent on digital distribution. The evolving nature of these policies creates ongoing compliance challenges that require continuous monitoring and adaptation.

The Solution: Building a Robust AI Governance Framework

The issues above may seem overwhelming, but studios can safely navigate them by creating appropriate internal AI governance systems. When well-structured, AI governance gives studios a framework for identifying and evaluating risks, setting clear policies, and ensuring compliance while preserving creative freedom. It helps teams stay aligned, protects valuable IP and player trust, while positioning the studio to adapt quickly as regulations and technologies change.

Here’s where to start:

Forming a Governance Committee. Effective AI governance requires coordination across multiple disciplines within game studios. Technical teams understand AI capabilities and limitations, legal counsel can identify regulatory requirements and legal risk, creative leaders ensure artistic integrity, and business stakeholders manage commercial and reputational risks. For midsized and larger studios, a dedicated AI governance committee ensures balanced oversight and informed decision making.

Risk Assessment and Compliance Gap Analysis. If a studio is already using AI tools, it should conduct a full audit of current AI usage and map these against applicable regulatory, contractual and policy obligations to identify compliance gaps and prioritize risk areas.

Policy Development and Documentation. Studios should create an AI policy tailored to their specific needs and risk profile. At a minimum, an AI policy should include the listing and classification of approved tools and use cases. High risk applications such as consumer-facing materials and AI systems and those affecting player safety, processing children’s or biometric data, involving digital replicas, or making hiring decisions should require enhanced oversight. For AI tools used in the generation of code or consumer-facing assets, the policy should require personnel to document the entire development process, including all prompts, outputs and edits. Audit-ready logs should be maintained in case it becomes necessary to demonstrate the extent of human involvement. The policy should address the use of AI notetakers and restrict personnel from feeding personally identifiable information, trade secrets, client information, and other confidential or proprietary materials into AI models without specific authorization. Finally, it should define reporting and mitigation procedures for compliance failures and establish processes for vetting new AI tools.

Third Party Risk Management. Game studios increasingly rely on third-party AI services, middleware, and development tools. Each vendor relationship creates potential compliance obligations and liability exposure that must be managed through contractual safeguards, due diligence processes, and ongoing monitoring. As part of their AI governance strategy, studios should implement vendor assessment frameworks that evaluate third-party AI providers based on data security practices, compliance capabilities, insurance coverage, liability allocation, service level guarantees and other key terms of use.

Training and Cultural Integration. All personnel should be trained on the AI policy, approved tools, risk scenarios and reporting and mitigation procedures.

Continuous Monitoring and Policy Evolution. AI governance should include mechanisms for periodic policy review and continuous improvement processes that adapt to technological and regulatory changes. Studios should adopt privacy-by-design and compliance-by-design principles to avoid costly retrofits and stay ahead of emerging requirements.

Final Thoughts

The integration of advanced AI into game development is rapidly becoming a standard practice, but the legal and regulatory landscape remains complex. Studios that proactively address AI governance can gain competitive advantages through reduced legal risk, stronger platform relationships, enhanced player trust, and development practices that safeguard IP and confidentiality.

The costs of inaction, including litigation, regulatory penalties, platform bans, reputational harm, and risks to IP and confidentiality, far outweigh the investment needed to implement strong AI governance. Studios that treat AI governance as a strategic advantage rather than a compliance hurdle will be best positioned to succeed in the AI-driven future of interactive entertainment. If you have any questions about AI policies or need help drafting one, we can help.