Startup Founders Are Using AI To File Patents. Here’s Where DIY Becomes A Liability.

By Michael Drapkin and Nathan Mutter

Patents offer a way for startups to build a competitive edge, draw in investors, and safeguard their breakthroughs. Yet, the traditional patenting journey remains costly, sluggish, and complex to navigate—especially for cash-strapped enterprises.

Artificial intelligence is shifting that dynamic. Founders can leverage general-purpose applications to scour existing patents, write up inventions, and churn out drafts resembling actual patent documents in mere minutes. Managing this workflow independently can look like a simple method for entrepreneurs to cut expenses.

However, AI capabilities remain uneven. While the technology excels at certain tasks, it routinely misses the legal and strategic nuances that dictate a patent’s commercial worth. A filing might seem polished while offering minimal actual security.

Take patent claims, for instance: they outline the legal boundaries of what competitors are barred from copying. Errors regarding claim scope often stay hidden until a buyer, investor, or rival digs into the startup’s intellectual property assets.

The central question is not whether early-stage companies ought to use AI, but rather how much founders can securely handle on their own versus when professional legal insight becomes indispensable.

Where AI can help startups save time and money

Entrepreneurs can employ AI to sort technical documentation, condense prior patents, and spot relevant prior art. Converting engineering notes into a structured invention disclosure, as an example, trims preparation overhead and lets legal counsel concentrate on strategy.

Yet, the potential goes beyond solo DIY efforts. Skilled counsel can weave AI throughout the entire pipeline—managing discovery, drafting, illustrations, and quality checks. AI assists attorneys in probing alternate implementations alongside inventors, spotting gaps in disclosures, and verifying backing for specific claims. Lawyers direct these activities, assess outcomes, and tie each phase to business objectives.

Such an integrated approach yields far more thorough applications with greater efficiency, setting itself apart from simply feeding prompts to a chatbot and handing the output to a lawyer for a quick review.

When DIY patent filing becomes a liability

• Incomplete provisional applications. A provisional filing date is only as strong as its underlying disclosure. Subsequent claims only inherit that timeline if the provisional thoroughly describes and enables the invention. A do-it-yourself draft might miss critical technical nuances, alternative setups, and variations needed for later claims. Appending those missing pieces later cannot retroactively mend the primary filing.
• Premature disclosure. Pitching to investors, showing off products, or publicizing breakthroughs ahead of filing can jeopardize patent rights, particularly overseas. Public exposure can also wipe out trade secret protections. Additionally, uploading secret invention specifics into AI systems without assessing data handling policies introduces fresh vulnerabilities.
• Unclear ownership. Handing paychecks to staff or contractors does not replace the need for formal invention assignment agreements. Secure these contracts when personnel come onboard rather than waiting for due diligence audits to reveal deficiencies. Founders must likewise assign pertinent work to the company and check for conflicting obligations tied to past employers or academic institutions. Gaps in ownership can easily derail fundraising or buyout deals.

Opting for the cheapest route to file is not necessarily the most prudent financial choice. A shoddily prepared submission builds a false sense of security while leaving core innovations unprotected.

When legal counsel matters

Attorneys help determine whether to patent an innovation or safeguard it as a trade secret, balance filing priorities against company budgets, and evaluate deadlines before public exposure or statutory time limits restrict options. For instance, an internal procedure that rivals cannot observe or reverse engineer might be better kept confidential.

Determining claim scope demands careful legal intuition. A fraud-detection claim pegged to a single algorithm leaves competitors free to deliver identical functionality through another method. Conversely, overly broad claims might overlap with existing tech. Valuable claims target what competitors are forced to do in order to compete. Ideally, a single identifiable rival can infringe upon them, and that infringement remains detectable and provable.

The technical specification must outline alternatives and variations that back broader claims down the road without unnecessarily shrinking their reach. While AI can assist, strategic human judgment must steer the process.

Why investors look beyond ‘patent pending’

Filing volume reveals little about actual commercial utility. Venture capitalists and acquirers look past pending application counts to examine three core areas:

• Do you own it? They demand signed assignments from key founders, staff, and contractors, ensuring no conflicting claims from past employers or universities exist.
• Does it protect your moat? Claims must cover the core business model rather than a transient feature slated to be phased out next year, backed by sufficient application detail.
• Can you enforce it? Claims should resist easy design-arounds, and any infringement must be realistically detectable and provable.

Making patent protection more accessible

The true value of AI lies not just in pumping out higher volumes of cheaper applications, but in broadening access to meaningful legal protection without abandoning professional judgment.

Founders ought to question how a firm merges its technological tools with legal oversight, rather than settling for whether AI is used at all. The response should clarify how the workflow bolsters both operational speed and substance.

Ultimately, the costliest misstep in patenting may be realizing too late that a self-filed application never truly secured the innovation underpinning 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

01Can AI completely replace a patent attorney for startups?

No. While AI tools can assist with research, organization, and drafting, they often miss crucial legal and strategic nuances necessary for establishing commercial value and enforceable patent claims.

02What are the risks of using AI for provisional patent applications?

DIY or purely AI-generated provisional drafts may omit critical technical details, alternative designs, and variations. If the provisional application fails to adequately describe the invention, you cannot retroactively fix the disclosure when filing later claims.

03How do investors view DIY patent filings?

Investors and acquirers look beyond application counts to evaluate clear ownership assignments, robust claim support for business models, and the enforceability of the intellectual property against competitors.

04Why is premature disclosure dangerous for startups?

Pitching investors or demonstrating products before filing can forfeit international patent rights and destroy trade secret protections. Sharing sensitive details with AI tools without checking their privacy policies introduces additional exposure.