How to Automate Patent Drafting with AI?

The emergence of artificial intelligence opened the door for countless new applications and tools, including AI tools for patent drafting, automated patent drafting, and AI patent drafting assistants. For example, AI may be used to assist with various tasks throughout the patent drafting process, including invention disclosure form creation, analysis, and enhancement; patentability reviews and assessments; and drafting applications.

How to Automate Patent Drafting with AI?

Invention Disclosures + AI

The patent application drafting process usually begins with some sort of invention disclosure. This could be an invention disclosure form, a transcript of a call with an inventor, some rough sketches of the invention, or simply some experimental data.

At the very outset, AI may be used in several ways to expedite and simplify the invention disclosure process and the patent process as a whole, including:

  • Expediting invention disclosure form creation. Here, some materials or invention disclosure resources may be inputted and then AI may be used to automate and expedite the drafting of custom invention disclosure forms, thereby helping inventors with filling out their invention disclosure forms.
  • Supplementing invention disclosures. AI may also be used to suggest alternative embodiments or applications, further assisting inventors and patent attorneys alike with protecting their invention and broadening the scope of their invention. Importantly, however, AI must be trained not to be inventive with its suggestions.
  • Clarifying aspects of the invention. AI is also helpful with generating clarifying questions for the inventor to answer, whether that’s before an inventor interview or simply a step in expanding the invention disclosure material.
  • Simplifying and expediting review of invention disclosure materials. AI may also be used to summarize and explain invention disclosure documents, thereby simplifying the review of invention disclosure documents for patent professionals.

Patentability Reviews + AI

Next, the patenting process may involve a patentability review or assessment. Here, the invention may be compared with known prior art or a patentability search may be conducted to determine relevant prior art that exists.

At this stage, AI may be helpful with the following tasks:

  • Prior art document analysis.  Here, AI may assist with analyzing prior art documenta and suggesting the novel aspects or inventive features of the invention.
  • Sample claim generation.  AI may also be used at this stage to generate some sample claims, which may be reviewed by a patent professional and inventor to determine the scope and value of possible patentable aspects of the invention. Generating sample claims prior to drafting an entire patent application.

Patent Application Drafting + AI

Additionally, when it comes to drafting applications, there are numerous ways in which AI may help, including the following:

  • Full application drafting. Some AI tools, including Solve’s Patent CopilotTM, can draft entire patent applications, output discrete and individual sections of a patent application, and/or convert patent applications for filing in different jurisdictions and patent offices. Here, for example, Solve’s Patent CopilotTM may generate an entire application or a section of a patent application (e.g., the claims) when prompted by an attorney or legal professional. Additionally, AI tools may be customized to draft in a particular style or tailored using example patent applications that have been previously filed.
  • Patent application revisions and editing. Additionally, AI tools are capable of revising or redrafting sections of a patent application, as well as expanding or further elaborating on sections of a patent application.
  • Figure editing and drafting. AI tools may also have built in figure editing and drafting capabilities. For example, Solve’s Patent CopilotTM can assist with the generation and creation of figures, including flowcharts.
  • Chemical structure and data input and analysis. AI is also capable of analyzing chemical structures and raw tabular data, and generating text, including an Examples section of a patent application.
  • Patent application review. AI may also be used to review patent applications, including helping with the review of patent claims, correcting antecedent basis issues, reviewing claim support and disclosure within a specification therefor, etc.

Benefits of AI for Patent Drafting

AI is being used by a wide range of legal professionals, patent drafters, and in-house teams around the world. Additionally, many users are reporting large efficiency gains from its implementations in their workflow.  Here are some overviews of the potential benefits that we are seeing at Solve:

  • Efficiency improvements. Significant time savings in drafting and reviewing patent applications.
  • Quality maintenance. Consistent, high-quality output tailored to individual preferences, despite cost and time pressures.
  • Strategic focus. More time freed up to spend on providing value-add strategic advice and decision-making, such as more time analyzing and developing higher quality claims, thereby delivering clients with a higher quality service with faster response times.
  • Increased bandwidth. Ability to handle more clients and cases.
  • Faster turnaround. Quicker analysis and enhancement of disclosures, and faster responses from outside counsel.
  • Strategic IP management. Receive better strategic advice for IP portfolio development from outside counsel, and free up time to weigh this advice with business objectives.
  • Enhanced ROI. Improved return on investment from IP due to strategic focus.
  • Prolific innovation. AI aids in generating more comprehensive patent applications and invention disclosures, and frees up inventor time to spend on R&D, rather than interacting with attorneys and filling out long disclosure forms.
  • Reduced barriers. Easier and less burdensome patenting process with a much-reduced back-and-forth between inventors, in-house teams, and outside counsel.
  • Competitive edge. Free up the time of your IP team and outside counsel to receive more strategic patenting advice tailored to your business objectives.

Potential Risks of AI Patent Drafting

Many AI systems, including Solve’s Patent CopilotTM, have been guard-railed to prevent errors and hallucinations.  Additionally, Solve’s Patent CopilotTM is designed to keep the attorney or legal professional in control during each step or use of AI.  However, there are still things legal professionals should watch out for when using AI during their patent application drafting process.

First, a patent professional should always still review the claims for completeness and accuracy. Specifically, the claims should be reviewed to make sure that at least one human significantly contributed to each claim.

Second, a patent professional should still review the specification for accuracy and completeness. Most AI patent drafting tools are designed to draft the specification such that it properly supports the drafted claims. However, AI tools are not a substitute for a patent professional and patent professionals should still review the specification to ensure that it properly supports and enables aspects of the claims, thereby ensuring that they comply with the relevant jurisdiction in which patent protection is being sought.

Conclusion

Overall, AI has vast potential to help various industries and workflows in intellectual property and patent law.  With that said, it must be designed and used in proper ways by legal professionals to effectuate great patent protection for inventors and clients.

If you are interested in streamlining the patent drafting process with Solve’s Patent CopilotTM, please contact us.

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Solve Intelligence Ranked #1 IP Platform by the World's Leading Law Firms

Solve Intelligence has been ranked the number one intellectual property platform in the latest Legal AI survey published by SKILLS (the Strategic Knowledge & Innovation Legal Leaders Summit). The study surveyed 130 leaders at the world's top law firms about their legal AI product usage across every major practice area, scoring platforms based on live deployments, active pilots, and tools under consideration. In the Patents/IP category, Solve Intelligence placed first with a weighted score of 67, making it the most widely-used platform in the category. See the full report here.

The Hidden Cost of Ignoring AI in Patent Practice

As patent practitioners, the choice to “do nothing” about AI is not a neutral act. 

Law firms or in-house counsel that delay the adoption of AI may believe they are minimizing risk, but oftentimes they are taking on a different set of less visible, long-term risks. 

These hidden costs can accumulate quickly, from compounding inefficiencies in traditional patent drafting workflows to missed revenue opportunities that remain untapped without leveraging AI-driven capabilities.

So, what can patent practitioners do to stay ahead of the game? Here is what the Solve Intelligence team has seen speaking with thousands of practitioners.

Key takeaways

  • Waiting to adopt AI is itself a strategic decision with compounding costs.
  • Manual patent workflows create time, quality, and knowledge bottlenecks that grow over time.
  • Firms already experimenting with AI gain operational insight that late adopters cannot shortcut.
  • Low-risk entry points let practitioners build confidence without compromising legal judgment.

Why Patent Attorneys Need Purpose-Built AI

Legal AI platforms like Harvey and Legora are valuable productivity tools. Powered by large language models and enriched with legal data sources, firm-specific knowledge, and purpose-built workflows, they perform well on tasks like legal research, document summarisation, and contract or email drafting.

But their workflows are optimised for breadth across practice areas, not for the structural, technical, and jurisdictional depth that patent work requires.

For IP teams that already have access to a generalist platform, or are trying one out, the natural follow-up question is whether a vertical solution adds enough to justify the investment. 

At Solve Intelligence, we build AI specifically for patent practitioners. In our experience scaling the platform to over 500 IP teams, there is no question that patent-specific tooling delivers ROI that generalist platforms alone cannot. This article sets out why.

Key takeaways

  • Generalist legal AI tools weren't trained for the structural depth patent work demands.
  • Solve Intelligence is shaped by in-house patent attorneys who joined Solve from firms like Carpmaels & Ransford and Fish & Richardson.
  • Custom templating lets attorneys match output to house style, client/technology area, or jurisdiction.
  • Generalist and patent-specific AI are complementary investments, not competing ones.

Marbury Law sees 3x-4x efficiency gain from using Solve Intelligence

When we sat down with Bob Hansen for this conversation, we knew it would be grounded in both legal depth and real-world business experience. Bob is a founding partner of The Marbury Law Group and has extensive experience across patent prosecution, litigation, licensing, portfolio strategy, and complex IP transactions. But what makes his perspective particularly compelling is that he also brings 20 years of real-world experience as an engineer, program manager, and business executive in Fortune 50 companies and start-ups. He understands firsthand how innovation moves from idea to product, and how intellectual property law fits into that journey.

That dual lens is exactly why we wanted to have this discussion. Bob evaluates technology not just as a patent attorney, but as someone who has managed engineering teams, navigated acquisitions and divestitures, raised capital, and built businesses. When someone with that background says AI has been transformative and backs it up with measurable 3 to 4x efficiency gains, it’s worth listening.

Key Insights

  • AI adoption requires proof. Bob and his team tested multiple tools before committing, and only moved forward once they saw quantifiable results.
  • 3 to 4x efficiency gains changed the business case. By tracking his own drafting time, Bob demonstrated that AI-enabled workflows made fixed-fee work viable at partner rates.
  • Demonstration drives adoption. Live drafting sessions, client transparency, and side-by-side cost comparisons created full buy-in from both clients and colleagues.
  • Integrated chat removes friction. Keeping research, drafting, and revisions inside one contextual workspace eliminated copy-paste workflows and saved significant time.
  • Context is a force multiplier. AI performs best when it understands the full invention disclosure, file history, and drafting materials in one place.
  • Speed expands strategic value. Faster drafting didn’t just save time - it enabled better coverage, stronger enablement, and real-time responsiveness to client needs.

About Marbury Law

The Marbury Law Group is a premier mid-size, full-service intellectual property and technology law firm in the Washington, D.C. area, with additional strength in commercial law, litigation, and trademark litigation. Recognized by Juristat as a top 35 law firm nationwide and holding Martindale-Hubbell’s AV® Preeminent™ Peer Review Rating, Marbury serves clients ranging from Fortune 500 companies and mid-size technology businesses to high-tech startups and inventors. Its practitioners bring unusually wide-ranging experience, including former technology executives, government R&D managers, startup founders, in-house counsel, “big-law” attorneys, USPTO patent examiners, and judicial clerks. 

Marbury delivers “big-law” service with the flexibility and personal attention of a smaller firm, pairing high-quality work with efficient, budget-aware billing. Based near the USPTO, the firm has drafted and prosecuted thousands of U.S. and foreign patent applications and trademarks, and advises on IP strategy, diligence, and licensing. Formed in 2009 through the merger of two established practices (with roots dating back to 1994), the firm takes its name from Marbury v. Madison (1803), the landmark Supreme Court case that established judicial review.