May 12, 2026
Artificial intelligence (AI) has moved rapidly from an emerging technology to a foundational component of modern business operations. With that growth has come an expanding set of intellectual property (IP) disputes. Throughout 2025, courts, regulators, and litigants increasingly confronted complex questions about how traditional IP frameworks apply to AI-enabled innovations. As we move into 2026, those issues are expected to deepen, creating both risk and opportunity for companies investing heavily in AI-driven tools, products, and creative outputs.
One of the most prominent issues in recent AI-related litigation concerns patent infringement and validity. AI systems often blur the lines among software, hardware, data, and decision-making processes. This makes it more difficult to define patentable subject matter, establish novelty, and assess obviousness. Disputes have increasingly focused on whether AI-enabled claims merely automate known processes or instead introduce genuinely inventive technical solutions. In infringement analyses, parties must now address the role of training data, model architecture, and human involvement in determining whether accused systems practice claimed elements. These technical nuances place a premium on expert engineering and scientific analysis to explain how AI systems are built, how they integrate or reshape existing software and hardware, and how it all functions in real-world environments.
Closely related are disputes involving ownership and protectability of AI-generated outputs. In 2025, litigation and administrative actions continued to test whether creative works generated by AI—such as text, music, images, and designs—qualify for copyright protection and, if so, who owns those rights. Many disputes attempt to untangle the degree of human authorship, the relationship to training content, the nature of prompts, and the level of control exercised over the AI system. These issues are expected to intensify in 2026 as AI-generated content becomes more prevalent in marketing, entertainment, and product design, particularly in cases involving alleged copying, derivative works, or misappropriation.
Another major litigation theme involves trade secrets and confidential data used in AI training and deployment. Lawsuits increasingly allege improper acquisition or use of proprietary datasets, source code, or model parameters. The issue especially becomes convoluted as employees move between competitors or when AI systems are trained on large-scale third-party data. In 2026, courts are likely to see a growing number of disputes that test questions as to whether training on certain datasets constitutes misappropriation, how to define reasonable secrecy measures in AI development, and how damages should be calculated when alleged misuse occurs at scale.
AI-centric IP litigation forces parties, and their experts, to face unique challenges in quantifying economic harm. Traditional damages theories—such as lost profits or reasonable royalties—must now be adapted to address AI-enabled products and services that often generate value indirectly through efficiency gains, analytics, or downstream innovation. In 2025, courts began grappling with how to apportion value between core AI functionality and surrounding systems, data, and human contributions. In 2026, experts will increasingly be asked to assess market impact, incremental productivity, and competitive advantage attributable specifically to AI components.
As AI continues to reshape innovation, IP litigation involving these technologies will demand interdisciplinary expertise that spans engineering, data science, economics, and legal standards. Secretariat is uniquely positioned to support law firms and their corporate clients in navigating these challenges.
Our experts provide rigorous technical analysis of AI systems for infringement and invalidity matters, assess ownership and protectability of AI-generated works, and deliver sophisticated damages modeling tailored to AI-driven business models. In appropriate cases, this work may also include evaluating testing and benchmarking evidence—such as comparative or A/B testing results—to assess technical performance claims, causation, and economic relevance in AI-related disputes.
Whether assisting in the protection of AI-based productivity tools, advanced analytics platforms, product enhancements, or creative outputs, Secretariat helps clients translate complex scientific and economic issues into clear, persuasive litigation support—today and as AI-related disputes continue to evolve in 2026 and beyond.
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