AI is reshaping patent litigation not just through efficiency gains but by amplifying both opportunities and challenges for enforcement. As outlined in a recent New York Law Journal article by my former colleague Rob Maier, 2026 is expected to be a record year for U.S. patent litigation, driven by pro-patent policies, AI tools, litigation funding, and rising jury awards. (Baker Botts analysis.) However, AI tools remain a wildcard, promising to enable rapid infringement detection while introducing new complexities like reliability issues and ethical oversight.
Broader ecosystem changes require further consideration. For instance, USPTO Director John A. Squires' centralization of IPR decisions has led to institution rates initially near 0%, rising to around 4% recently as of December 2025, making patents more robust and enforcement more favorable. (Patently-O analysis.) This environment, combined with AI's capabilities, could fuel a surge but only if firms address its pitfalls.
AI Is Accelerating Patent Enforcement
For years, patent enforcement was bottlenecked by the need to manually sift through portfolios and products, traditionally a resource-intensive process. AI tools are changing this by enabling scalable analysis of vast datasets, from patents to public product specs, to spot potential infringements.
AI tools like Patlytics, Patsnap, and PQAI accelerate enforcement through semantic searches for prior art, infringement detection with claim charts, and invalidity analysis, reducing analysis time substantially (e.g., 40-80% in various tasks, per tool providers) and supporting pre-suit strategies. (Patlytics; Patsnap; PQAI.) However, risks like biases require human validation. (Duke Law analysis.) Nevertheless, useful results can be obtained faster than ever, with more comprehensive coverage, uncovering non-obvious connections that human teams might miss.
AI-Powered E-Discovery Comes of Age
AI is maturing in e-discovery, slashing review timelines by automating document classification and privilege detection. Tools like those integrated with platforms such as Thomson Reuters' CoCounsel Legal can process large volumes of data for litigation discovery, flagging relevant elements in reduced time. (Thomson Reuters announcement.)
Yet, limitations persist: Beyond hallucinations, AI in discovery faces scrutiny for indefiniteness in patent claims and data-intensive demands, often requiring extensive preservation of training datasets during litigation. In complex tech fields like drug discovery, AI-assisted patents risk enablement-based invalidity defenses in litigation impacting 2026 cases, where courts post-Amgen may question if disclosures teach replication without undue experimentation. (Venable analysis.)
To add nuance, successful adoption involves hybrid models: AI for initial triage, humans for final judgment, ensuring accuracy as well as compliance with emerging court rules on AI transparency.
AI in Research and Patent Analysis
AI enhances research by leveraging semantic tools to reveal hidden prior art, as seen in platforms like Patsnap, which map tech relationships across industries. (Patsnap overview.) Predictive analytics further refines strategy, modeling judge tendencies and damages. (Lex Machina.)
Notably, these tools amplify biases if trained on skewed data, potentially undermining case equity. (Duke Law study.) Careful implementation should consider emerging challenges: As AI-augmented invention becomes more prevalent in fields like drug discovery, commentators suggest patent law may need to adapt definitions of "ordinary skill" to account for AI tool proficiency. (IPWatchdog commentary.)
Ethical Considerations in AI Use
As AI integrates deeper into patent practice, ethical responsibilities grow. Firms must address inventorship risks in litigation, ensuring for example human conception in accordance with evolving legal guidelines to fend off a potential source of invalidity defenses impacting 2026 cases. Compliance with emerging court rules and standing orders on disclosing generative AI tool usage in filings and discovery is also increasingly important. (Venable guidance.) This involves auditing for biases and ensuring transparency to avoid sanctions, positioning ethical AI adoption as a competitive differentiator.
Policy Shifts Amplify AI's Impact
Policy shifts at the USPTO, including Director Squires' oversight, have reduced IPR institutions significantly in 2025, with rates initially near 0%, rising to around 4% recently, and overall well below historical norms (under 40% in some periods), bolstering patent value. (Patently-O report.) These include a bifurcated institution process and proposed categorical bars to limit repeat challenges. Revised AI inventorship guidance further solidify this pro-patent stance, clarifying rules for USPTO examination and, if adopted by courts, bolstering value of litigating patents on emerging technologies. (USPTO guidance.) Potential SCOTUS reviews or legislative reforms like PERA could further clarify AI eligibility under §101, impacting 2026 cases. (Lexology analysis.)
Litigation Funding Meets AI
Litigation funding now exceeds $19B globally, with patents and commercial litigation claiming a significant and growing share, projected to hit $53.2B by 2035. (Research Nester report.) Juries awarded a record $4.3B in 2024 across over 90 cases. With notable 2025 awards like $634M in Masimo v. Apple, and funding projections to $53.2B by 2035, the cycle intensifies, although appeals add risks. (Masimo statement; market analysis.)
The combination of abundant capital, record verdicts, and AI-driven case surfacing thus creates a self-reinforcing cycle fueling filing surges.
What This Means for 2026
Looking forward, patent litigation in 2026 will likely be:
- More numerous: AI identifies opportunities earlier, with scrutiny on validity.
- Faster: Shorter e-discovery and research timelines, tempered by ethical audits.
- More strategic: Predictive analytics inform decisions, critiqued for overconfidence.
- More scrutinized: Courts demand AI use documentation, with oversight essential.
Firms that integrate AI deeply, while maintaining oversight and documentation, will have a competitive edge. Those that treat AI as an accessory rather than a strategic core will struggle to keep pace.
Bottom Line
AI is no longer an auxiliary tool in patent litigation. It has become foundational—driving discovery, research, strategy, and even the number of cases that get filed, while demanding vigilance against biases and errors.
2026 won't just be the year AI transforms patent practice. It will be the year firms must balance its power with rigorous human oversight to reshape the enforcement landscape.