Artificial intelligence tools have made their way into nearly every corner of business operations, and patent drafting is no exception. Founders, product teams, and even some attorneys are experimenting with AI to produce patent application drafts faster and at lower cost. On the surface, the output looks impressive. The language is polished. The formatting is clean. But beneath that professional veneer, the pitfalls of AI-generated patent applications are significant, and they can cost inventors the very protection they set out to secure.
At Gallium Law, our registered patent attorneys are seeing a growing number of AI-drafted applications cross our desks for review. The pattern is consistent: these drafts look competent at first glance but fall apart where it matters most, under the scrutiny of a USPTO examiner, a competitor’s legal team, or a federal court. If you are considering using AI to draft or assist with a patent application, understanding these risks before you file could save you years of prosecution headaches and thousands of dollars in wasted fees.
Have questions about a patent application you are preparing? Contact Gallium Law today to speak with an experienced patent attorney.
The Enablement Problem That AI Cannot Solve
Of all the issues we see with AI-generated patent applications, the enablement requirement is the most consequential and the most consistently missed.
Under 35 U.S.C. § 112, a patent application must contain a written description that enables a person of ordinary skill in the art to make and use the claimed invention without undue experimentation. This is not a formality. It is a substantive legal standard that the USPTO and federal courts enforce rigorously. The Supreme Court reinforced this in Amgen v. Sanofi (2023), holding that broad functional claims require correspondingly broad enablement, and that describing a goal is not the same as teaching someone how to achieve it.
AI drafting tools struggle with enablement because they are trained to generate text that reads well, not text that teaches well. A large language model can produce a specification that describes what an invention does in convincing detail. What it consistently fails to do is explain how the invention works with enough technical depth and breadth to satisfy the enablement standard.
This is the gap Gallium Law sees most frequently. An AI-drafted application might describe a single embodiment clearly enough, but it rarely provides the range of embodiments, alternative implementations, and boundary conditions needed to support claims of meaningful scope. The result is an application that either faces rejection during prosecution or, worse, receives a patent with claims so narrow they offer little practical protection.
A patent that does not enable the full scope of its claims is a patent that competitors can design around. Understanding how patent prosecution works and what examiners look for during examination is essential context for anyone tempted to hand this process off to a machine.
For example, AI-generated applications consistently fail to produce a meaningful list of hardware components required to implement an invention to the standards required by 35 U.S.C. § 112. Consequently, these applications may face fatal rejections at the USPTO. Even worse, if the patent is allowed, they may be invalidated in federal court or in a subsequent invalidation proceeding before the USPTO, thereby wasting thousands of dollars and countless resources.
Shallow Claim Drafting and the Breadth Problem
Patent claims define the boundaries of your legal protection. They are, in many ways, the entire point of the application. Everything else in the document exists to support and enable those claims. And this is where AI-generated applications reveal their most dangerous weakness.
AI tools tend to produce claims that are either too narrow or too broad, with very little of the strategic middle ground that experienced patent attorneys spend years learning to navigate. Narrow claims protect only the specific embodiment described, which means a competitor can make a minor tweak and avoid infringement entirely. Overly broad claims, meanwhile, invite rejections based on prior art or, if they somehow issue, create enforcement nightmares when challenged in litigation.
Skilled patent claim drafting is a layered process. It starts with broad independent claims that capture the core inventive concept, then builds dependent claims that progressively narrow the scope, creating fallback positions if the broadest claims are challenged. This structure is both strategic and deliberate. It anticipates how the patent examination process will unfold and how the claims might need to be defended years later.
AI-generated claims almost never exhibit this kind of strategic architecture. The tools produce claims that look syntactically correct but lack the prosecution awareness and enforcement foresight that come from working with real inventions in actual legal proceedings.
Written Description Deficiencies That Surface During Prosecution
The written description requirement under 35 U.S.C. § 112 is related to but distinct from enablement. While enablement asks whether the specification teaches someone to make and use the invention, the written description requirement asks whether the specification demonstrates that the inventor actually possessed the invention at the time of filing.
AI-generated applications often fail this test in subtle ways. Because the tool is synthesizing language from patterns rather than from an understanding of the actual invention, the resulting specification can be vague, internally inconsistent, or missing critical details that a patent examiner will flag during prosecution.
For example, an AI tool might describe a mechanical assembly using language that sounds technically precise but glosses over how specific components interact under real-world conditions. Or it might describe a software process without specifying the data structures, algorithms, or computational steps that make the process work. These gaps become painfully apparent when an examiner issues an Office Action demanding clarification.
Once a patent application is filed, you generally cannot add new matter to the specification. This means that written description problems in the original filing can haunt you throughout prosecution, limiting your ability to amend claims or respond to rejections effectively. The duty of disclosure and candor obligations that apply to every patent applicant further complicate matters, because you cannot simply patch over deficiencies with post-filing arguments.
Prosecution History Risks That Compound Over Time
Every communication between an applicant and the USPTO during prosecution becomes part of the patent’s file history. This record is permanent, and it matters enormously if the patent is ever asserted in litigation.
Under the doctrine of file history estoppel, statements and amendments made during prosecution can limit the scope of a patent in enforcement. If you narrow your claims to overcome a rejection, you may be barred from later arguing that the surrendered subject matter is still covered under the doctrine of equivalents.
AI-generated applications create outsized prosecution history risk because they often require extensive amendment during examination. When the specification lacks sufficient enablement or the claims are poorly structured, the back-and-forth with the examiner generates a long, messy prosecution record full of concessions and narrowing amendments. Each of those concessions becomes potential ammunition for a defendant in future litigation.
An application drafted with enforcement strategy in mind from the start avoids this trap. Experienced patent attorneys draft specifications and claims that anticipate likely rejections and build in room to respond without surrendering meaningful scope.
What AI Gets Wrong About Patent Figures and Technical Disclosure
Patent applications are not just text documents. Technical drawings, flowcharts, and schematic illustrations are often critical components of the disclosure, and in many cases, they provide the enablement support that the written description alone cannot.
AI tools are primarily language generators. They may produce passable boilerplate descriptions referencing figures, but they do not generate the figures themselves, and they rarely account for the relationship between text and illustration that patent examiners expect. The result is a specification that references “FIG. 1” or “FIG. 2” without ensuring that the figure actually supports the claims in the way the text suggests.
This disconnect is more than an aesthetic issue. In prosecution, examiners rely on figures to understand the invention. In litigation, courts look at figures to interpret claim scope. A mismatch between the text and the figures, or a set of figures that fails to illustrate the full breadth of the claimed invention, can undermine the entire application.
Understanding the differences between design patents and utility patents makes this point even clearer. For design patents, the drawings are essentially the entire disclosure. For utility patents, the drawings must work in concert with the specification to provide a complete picture. AI tools simply are not equipped to manage this relationship effectively.
The False Economy of Cutting Corners on Patent Drafting
One of the primary appeals of AI-generated patent applications is cost savings. A tool that produces a draft in minutes instead of weeks looks like an obvious win for budget-conscious inventors and startups. But the math changes dramatically when you account for the downstream costs.
Office Action responses are expensive. Each round of prosecution can cost thousands of dollars in attorney fees, and AI-generated applications tend to require more rounds than well-drafted ones. If the application ultimately fails to issue, or issues with claims too narrow to be useful, the filing fees, prosecution costs, and opportunity costs are all lost.
There is also the cost of the patent you did not get. A well-drafted application with broad, enforceable claims is a business asset that can generate licensing revenue, strengthen your competitive position, and increase the valuation of your company. A weak patent with narrow claims or a messy prosecution history may, in practical terms, be barely better than no patent at all.
Startups and early-stage companies are especially vulnerable here. Your first patent applications often set the tone for your entire IP portfolio. Starting with AI-generated drafts that need to be fixed, abandoned, or refiled is not a shortcut. It is a detour that costs more in the long run.
Want to make sure your patent application is built on a strong foundation? Fill out our Contact Form to get in touch before you file.
How Human Expertise Fills the Gaps AI Cannot
None of this means AI has no role in the patent process. Tools that help with prior art research or initial brainstorming can be useful when guided by an experienced hand. The problem is treating AI as a replacement for the specialized legal and technical judgment that patent drafting demands.
A registered patent attorney brings knowledge that no language model can replicate: an understanding of how examiners think, how courts interpret claim language, and how a single phrase in a specification can determine whether a patent is worth millions or worth nothing.
At Gallium Law, our attorneys and agents work directly with inventors to understand the technical substance of each innovation before a single word of the application is written. We draft specifications with enablement, prosecution strategy, and enforcement potential all in view.
If you are weighing whether to involve a patent attorney or rely on AI tools, we are happy to review what you have and give you an honest assessment. That conversation could be the most valuable step in your entire patent process.
Frequently Asked Questions
Can I use AI to draft a patent application and then have an attorney review it?
You can, and some inventors do take this approach. However, the review process often ends up being more time-consuming and expensive than drafting from scratch. AI-generated applications typically require substantial rewriting to meet enablement and written description standards, and structural claim issues often require rebuilding the claims entirely rather than editing them. Starting with an attorney-drafted application usually produces better results at comparable or lower total cost.
Are AI-generated patent applications valid if they get approved by the USPTO?
A patent that issues from an AI-generated application is legally valid, but validity and enforceability are two different questions. Patents with thin enablement, weak written descriptions, or messy prosecution histories are far more vulnerable to invalidation challenges in litigation. A patent that cannot survive a validity challenge offers little practical protection for your invention.
Does Gallium Law help fix patent applications that were initially drafted using AI tools?
Yes. Our patent attorneys regularly help clients who started with AI-generated drafts and realized they needed professional assistance. Depending on the status of the application, we may be able to strengthen the specification and claims through continuation applications, requests for continued examination, or other prosecution strategies. The earlier you involve experienced counsel, the more options are available.
Protect Your Innovation With Patent Applications Built to Last
The temptation to use AI for patent drafting is understandable. The technology is fast, accessible, and produces output that looks convincing. But looking convincing and being legally sound are fundamentally different things. The enablement gaps, claim structure weaknesses, and prosecution risks that come with AI-generated applications can turn what seems like a cost-saving decision into an expensive lesson.
Your inventions deserve protection that holds up when it matters most: during examination, in licensing negotiations, and in the courtroom. Gallium Law’s award-winning patent team combines deep technical knowledge with strategic legal experience to build patent applications that work as hard as the innovations they protect.
Call 651-256-9480 today, fill out our online consultation form for a free, confidential consultation, or visit galliumlaw.com to learn more about how we help inventors and businesses build lasting IP protection.