How AI Is (and Isn’t) Transforming Patent Practice

Walk into any intellectual property conference in 2025, and you’ll hear one topic echoing across sessions and expo halls: artificial intelligence. 

From flashy vendor demos to panel debates, AI is firmly at the center of the conversation. But behind the buzz, the reality is more measured. Adoption of AI in IP practice is advancing — cautiously and deliberately.

Early AI use focuses on practical applications

Law firms and corporate legal departments are actively exploring AI tools, but for now, most deployments remain confined to practical, back-office tasks rather than transformative, client-facing work. Much of this early adoption centers on improving efficiency in day-to-day operations. Teams are using AI to automate docket entries, extract data from IDS forms, draft standard communications, and organize large volumes of patent files. While these applications might seem mundane, they play a crucial role in reducing administrative burdens and freeing up time for higher-value legal work.

Lack of trust looms large

Despite growing interest, significant caution still surrounds the broader use of AI in legal practice. Firms and corporate teams are grappling with several major concerns that continue to temper enthusiasm. One critical issue is confidentiality, as sensitive client or company data must remain secure and protected from potential breaches. Equally important is the question of accuracy and liability; errors in AI-generated work could expose firms to malpractice claims or costly rework. Moreover, there’s a strong expectation from clients and courts for transparency and explainability in legal processes, making “black box” AI outputs problematic. Generative AI, in particular, is viewed with a mix of intrigue and wariness. Although many practitioners are interested in leveraging it for research, analytics, and portfolio insights, few are comfortable deploying such tools unsupervised in client-facing matters.

Law firms eye efficiency gains

Within law firms, current AI pilots are primarily focused on achieving greater internal efficiency rather than transforming client services. The hope is that these tools will reduce the number of hours associates spend on repetitive tasks, lower overhead costs associated with routine patent prosecution work, and provide early-stage decision support for strategic planning. However, despite these clear goals, broad implementation remains limited. Ethical rules, heightened client expectations, and concerns over potential liability all contribute to a cautious approach toward integrating AI more deeply into everyday legal practice.

Patenting AI remains complex

Meanwhile, patent professionals face another AI challenge: protecting AI inventions themselves.

Corporate counsel report tension between fast-moving R&D teams and a legal system that’s still grappling with fundamental questions about inventorship, eligibility, and claim scope for AI-based technologies.

The most common hurdle at the USPTO for AI-based inventions is rejections under 35 U.S.C. § 101, which focus on patent subject matter eligibility. Examiners frequently characterize these inventions as abstract ideas, citing mathematical concepts, mental processes, or methods of organizing human activity. 

While the overall USPTO allowance rate sits at 76.53%, applications facing a § 101 rejection drop by more than 10 percentage points to 65.93%. Although § 101 rejections declined after the 2019 Revised Patent Subject Matter Eligibility Guidance, they’re climbing again. Defining what constitutes an “abstract idea” remains subjective and unpredictable, particularly for fields like AI and software, where technological and legal boundaries continue to blur.

A slow but inevitable transformation

Despite the hurdles, few doubt that AI will eventually reshape IP practice. The transformation, however, will be gradual.

For firms and companies, the path forward lies in moving ahead cautiously, establishing strong internal policies, carefully selecting vendors, and fostering close collaboration between legal, technical, and business teams.

In the coming years, organizations that balance innovation with risk management are likely to be best positioned to thrive in an AI-driven IP landscape.

In the coming years, the firms and legal departments that strike the right balance between innovation and risk management are likely to be the ones best positioned to thrive in an AI-driven IP landscape.