How AI Patent Filing Can Backfire for Startups

By Michael Drapkin and Nathan Mutter

While patents offer startups a way to protect innovations, build a competitive edge, and draw investors, the conventional patenting process remains costly, sluggish, and complex—especially for resource-constrained businesses.

Artificial intelligence is shifting that paradigm. Generalist AI platforms can examine existing patents, outline inventions, and draft documents resembling patent filings within minutes. For founders, handling this workflow independently can feel like a simple cost-saving measure.

However, AI capabilities are uneven. While these tools excel at certain tasks, they frequently overlook critical legal and strategic nuances that dictate a patent’s commercial worth. Consequently, an application might appear polished while offering negligible protection.

As an illustration, a patent’s claims establish its legal limits and determine what competitors can be legally barred from doing. Errors regarding claim scope often remain hidden until an investor, prospective buyer, or rival closely examines the enterprise’s intellectual property.

The central dilemma for startups isn’t whether to use AI, but rather how much founders can manage safely on their own versus when professional legal counsel becomes indispensable.

Where AI can help startups save time and money

Founders can leverage AI to structure technical documentation, distill existing patents, and spot relevant prior art. Transforming engineering logs into a structured invention disclosure, for instance, can cut preparation expenses and allow legal counsel to concentrate on higher-level strategy.

Yet the utility goes beyond mere do-it-yourself efforts. Qualified counsel can integrate AI throughout the entire workflow, managing invention discovery, drafting, illustrations, and quality checks. AI assists attorneys in investigating alternative implementations alongside inventors, spotting gaps in disclosures, and verifying support for claims. Lawyers can direct these tasks, assess the outcomes, and tie every phase back to business protection.

This integrated approach yields far more thorough applications with significantly greater efficiency, contrasting sharply with generating a draft via chatbot and merely having a lawyer review it later.

When DIY patent filing becomes a liability

• Incomplete provisional applications. A provisional filing’s early priority date is only as valuable as its underlying disclosure. Subsequent claims inherit that date exclusively if the provisional thoroughly details and enables the claimed invention. A self-drafted document may leave out essential technical variations, alternatives, and details required for future claims. Appending those elements later cannot retroactively fix the initial disclosure.
• Premature disclosure. Pitching to investors, showcasing products, or publicizing developments prior to filing can jeopardize patent rights, particularly on an international scale. Public disclosures can also strip away trade secret protections. Furthermore, sharing confidential invention information with AI platforms without checking their data practices introduces added vulnerabilities.
• Unclear ownership. Compensating an employee or contractor does not equate to securing proper invention assignment agreements. Startups must execute these contracts when individuals join rather than waiting for due diligence to reveal gaps. Founders must also assign relevant work to the enterprise and check for lingering duties owed to past employers or academic institutions, as ownership flaws can derail financing or acquisitions.

The least expensive filing method is not necessarily the most economical choice. A poorly constructed application generates a false sense of security while leaving core innovations vulnerable.

When legal counsel matters

Attorneys help determine whether to patent an innovation or keep it as a trade secret, prioritize filings within a set budget, and evaluate deadlines before disclosures or filing rules eliminate potential options. For instance, an internal procedure that rivals cannot observe or reverse engineer might be better preserved as a trade secret.

Determining claim scope demands precise strategic judgment. A fraud detection claim bound to a single algorithm may leave competitors free to offer identical functionality using alternative methods. Conversely, overly broad claims might conflict with established technology. Valuable claims target the exact actions competitors must take to rival the business—ideally where a specific, identifiable competitor’s infringement can be easily spotted and proven.

Furthermore, the specification must outline alternatives and variations to back broader claims down the road without unduly restricting their breadth. While AI can aid this process, strategic insight must lead the effort.

Why investors look beyond ‘patent pending’

Filing volume indicates very little about actual commercial worth. Investors and potential buyers look past the count of pending applications to evaluate several key factors:

• Do you own it? They demand executed assignment documents from all relevant founders, staff members, and independent contractors, free of competing claims from universities or former employers.
• Does it protect your moat? The claims must secure what the enterprise relies on—not a transient feature slated for removal next year—and the filing must supply enough detail to back those claims up.
• Can you enforce it? The claims should be difficult for others to design around, and any infringement must be realistically detectable and provable.

Making patent protection more accessible

The greatest advantage of AI is not simply mass-producing applications at a lower price point, but rather making robust protection more attainable without sacrificing sound legal judgment.

Founders should inquire how a law firm blends its AI instruments with human legal expertise, rather than simply checking if AI is utilized at all. The response should clarify how that methodology enhances both efficiency and substance.

Ultimately, the costliest intellectual property mistake may be realizing too late that a self-filed application never truly safeguarded the foundation of the business.

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Michael Drapkin is a founding partner of Landfall IP, an AI-native patent law firm based in Boulder, Colorado. He previously founded one of the largest electronics and computer patent prosecution practices in the U.S. at an Am Law 100 firm and was named U.S. Patent Practitioner of the Year by Managing IP in 2022.

Nathan Mutter is managing partner and founder of Landfall IP, an AI-Native law firm. He has served as top outside counsel at Oura, Coinbase, Rubrik, Salesforce 1 and many others. Mutter pioneered the creation of automation systems and tools that enhance efficiency across all aspects of legal services. His clients include both startups and large public companies.

Photo by Conny Schneider on Unsplash

Frequently Asked Questions

• Can startup founders use AI to file patents completely on their own? Yes, general-purpose AI tools can draft applications in minutes, but doing so without legal oversight can create significant liabilities and leave innovations unprotected.
• What are the main risks of DIY provisional patent applications? DIY drafts often omit critical technical details, alternatives, and variations, and missing information cannot be retroactively added to the original filing date.
• How can premature public disclosures harm a startup’s patent rights? Pitching to investors or showing products before filing can forfeit patent rights internationally and destroy trade secret protections.
• What do investors look for beyond a “patent pending” status? Investors look for clear ownership via signed assignments, proof that the claims protect the core business moat, and evidence that the claims can be enforced.
• How should law firms use AI in the patent process? Qualified counsel can use AI to manage invention discovery, drafting, and quality checks while providing the necessary strategic legal judgment.

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