The Evolving And Expanding Role Of AI In US Patent Litigation

(January 12, 2026) - Barnes & Thornburg attorneys Lauren Baker and John W. Cox examine the practical uses, benefits, and challenges of using artificial intelligence in U.S. patent litigation.

Introduction

Artificial intelligence (AI) has become a transformative force in many industries. Its impact on the legal field — including in patent litigation in the US — is both evolving and expanding. This article examines the practical uses of AI in patent litigation, focusing on where these technologies are making a difference and what challenges accompany their adoption.

Practical uses and benefits of AI in US patent litigation

AI is increasingly used to optimize various stages of patent litigation, providing significant efficiencies, increasing accuracy, and assisting with strategic decision-making. Below are several key applications and benefits:

Discovery and legal research

AI accelerates e-discovery processes by rapidly analyzing vast document sets — scanning millions of pages in mere hours, compared to traditional human review that could take months. AI tools can streamline privilege reviews and help identify and prioritize key facts and evidence using predictive coding models, substantially reducing hands-on attorney time. AI tools can go beyond simple keyword searches, discovering pertinent cases, patents, and administrative opinions that might otherwise be missed.

This leap in efficiency translates to important cost savings when compared to conventional models dependent on attorneys spending hundreds of billable hours on routine review tasks. Instead, AI handles these tasks under attorney oversight, freeing up legal professionals for higher-value work.

Prior art searches and invalidity contentions

Conducting prior art searches and formulating invalidity contentions has long been a labor-intensive process prone to human error, often missing critical non-patent literature (NPL) or documents in foreign languages. AI improves this process by rapidly searching global repositories — including scientific literature, product manuals, and open-source code — to find conceptually similar documents even in foreign languages.

AI can go beyond mere keyword searching to detect functional similarities even when terminology differs from the asserted patent(s), and predictive ranking can help attorneys prioritize results with greater precision. When preparing invalidity contentions, AI can identify prior art gaps and even propose alternative combinations to support obviousness arguments.

Offensive claim charts and infringement mapping

AI can aid in the preparation of infringement charts, including by analyzing large volumes of documents and applying claim language against product manuals, labels, and specifications to identify similarities and differences in the asserted patents and accused products or processes.

Claim construction

Claim construction, a key issue tied to case outcomes, can benefit from AI-driven analytics. Such tools analyze patents and court decisions for context and treatment of claim terms, and can identify technical equivalent synonyms and variants. AI can also mine past legal decisions to extract patterns and precedent for claim terms litigated often.

Litigation support and analytics

AI also assists with routine document drafting, including outlines for depositions and expert reports, and can generate visual representations to support expert testimony.

Litigation analytics platforms provide attorneys with predictive insights regarding judges, courts, and outcomes, refining strategic decisions and damages modeling based on prior rulings and tendencies.

Limitations and risks of using AI in US patent litigation

While AI offers substantial promise, it also introduces complexities and risks:

Complexity and unfounded reliance

Relying heavily on AI-generated discovery, legal research, or case summaries can backfire. Attorneys must remain wary of the limits of AI and courts' expectations for accuracy. Judges can — and have — sanctioned parties for submitting unverified AI-generated evidence, particularly when based on fake citations.

There has been significant press and commentary regarding false outputs or so-called "AI hallucinations" (e.g., nonexistent case citations). Problems with training data can introduce bias, and the performance of AI with foreign and historical documents remains limited.

Confidentiality concerns

Handling privileged or work-product protected material in cloud-based AI tools may risk waiving privilege. Data security is also a concern, particularly if platforms train their models on user inputs without explicit agreements prohibiting it. There is risk of inadvertently exposing invention details or litigation strategy.

It is always best practice to get explicit client consent before using AI tools in litigation to preserve both privilege and confidentiality.

Mitigation strategies and best practices

To use AI safely and effectively in patent litigation, attorneys should:

• Cross-check all AI-generated outputs;
• Treat AI as a triage agent — a first-pass tool — but never as the final authority;
• Apply independent legal judgment and maintain documented oversight;
• Clearly indicate that AI outputs are reviewed and edited by attorneys to preserve privilege;
• Use AI tools that guarantee data segregation and prohibit reuse of inputs for training; and
• Confirm all vendor policies around data privacy and security.

Key takeaways and considerations for the future

AI has emerged as a powerful tool in patent litigation, capable of transforming discovery, research, and strategy. But it is only as reliable as its inputs and human oversight. Policies and legal standards are rapidly evolving, and questions remain about how US law will adapt to these new technologies. For example, there could be new evidentiary standards for AI-generated expert analyses, akin to Daubert challenges focused on the black box nature of machine learning.

The US legal community — with its unique and extensive discovery processes — should also consider approaches taken in Europe or Asia regarding AI in litigation, especially as the technology and relevant laws continue to evolve. As AI technologies permeate patent litigation, thoughtful adoption — combined with careful consideration of risks and best practices — will be crucial for litigation counsel.

Conclusion

The integration of AI into US patent litigation brings both substantial benefits and novel challenges. By remaining vigilant, applying rigorous oversight, and adapting to emerging standards, attorneys can harness AI's power to increase efficiency and improve outcomes while mitigating risks. As the field continues to evolve, staying informed and proactive will be essential for successful litigation strategies in an AI-enabled future.

Originally published by Thomson Reuters Westlaw Todayon the 12^th of January , 2026.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.