AI and the Future of Patents

As artificial intelligence continues to accelerate the pace of innovation, the intersection of AI and intellectual property law is quickly becoming one of the most dynamic and consequential areas of legal practice. At the forefront of this evolution are Large Language Models (LLMs), which are beginning to transform how inventors and legal professionals approach the preparation of U.S. patent applications. The capabilities of LLMs offer the potential to enhance the clarity, structure, and efficiency of patent drafting, thereby making the patent process more accessible to a broader group of innovators. For inventors seeking to articulate their contributions with precision and detail, AI tools represent a promising resource that could streamline the path from idea to protection.

That said, the integration of AI into the patent application process raises important legal and policy concerns that should not be overlooked. Chief among them is the issue of inventorship. Under current U.S. patent law, only natural persons may be named as inventors. This statutory limitation creates legal uncertainty when AI systems—particularly LLMs—substantively contribute to the drafting or conceptualization of an invention or application. This emerging challenge strikes at the heart of long-standing doctrines in patent law and may ultimately necessitate legislative updates to more accurately reflect the modern innovation process, where human and machine collaboration is increasingly common.

Beyond questions of inventorship, the quality and reliability of AI-assisted patent drafting must be examined critically. While LLMs excel at generating coherent and well-structured text based on large datasets, the drafting of patent claims, specifications, and legal arguments still requires a nuanced understanding of patentability, precedent, and regulatory compliance.

The risk of omitting key limitations, mischaracterizing prior art, or crafting overly broad claims underscores the continued importance of human oversight. A balanced integration of AI with legal expertise may prove to be the optimal path forward—one that preserves legal rigor while leveraging the speed and analytical power of AI tools.

Additional considerations are both ethical and practical in nature. Transparency in the use of AI, accountability for errors, and potential biases embedded in AI outputs must be addressed thoughtfully. Moreover, integrating AI into existing patent workflows requires careful planning, from training and validation to ongoing compliance with USPTO guidelines. These considerations will shape not only how AI is used in practice but also how its use is perceived by examiners, courts, and other stakeholders.

Ultimately, the rise of LLMs in the patent drafting process is not merely a technical development—it reflects a broader shift in how we conceptualize creativity, authorship, and innovation in the 21st century. For attorneys, inventors, and policymakers alike, this moment offers an opportunity to engage with new tools while reaffirming the legal principles that protect and encourage innovation. As we navigate this transition, thoughtful collaboration between legal professionals and technologists will be essential.

For those exploring the legal implications and strategic advantages of using large language models in U.S. patent practice, Patent Attorney Derek Fahey is available to discuss how these technologies may affect your filings and intellectual property strategy. You can reach Derek at [email protected] for further guidance and insight on this rapidly evolving issue.