8 Critical Patent Application Mistakes That Can Cost You Protection

Learn how to avoid 8 common mistakes companies make when filing a patent application. This article highlights critical pitfalls that can jeopardize your IP protection and offers practical tips and tools.

8 Critical Patent Application Mistakes That Can Cost You Protection

Filing a patent application is one of the most strategic steps a company can take to protect its innovation. Yet, many businesses underestimate just how complex and nuanced the patent application process can be. Even small missteps—often made with the best of intentions—can lead to rejections, delays, or potentially weaker protection.

Here are eight patent application pitfalls companies often encounter when preparing to file a patent application. Whether you're handling the process with your in-house legal team, or working closely with external IP counsel, being aware of these pitfalls can make the difference between a strong, enforceable patent and one that struggles through examination.

1. Failing to Anticipate Prior Art Challenges

One of the most frequent reasons for patent application rejections is existing prior art—earlier patents or publications that are similar to your invention. It’s easy to assume your idea is novel, especially if it’s not widely known in your industry, but the patent office may uncover prior disclosures that raise serious challenges.

Thorough prior art analysis—ideally early in the process—can help you refine your invention’s positioning and avoid common grounds for rejection. 

2. Overly Narrow or Overly Broad Claims

The claims define the scope of protection sought for the patent application. Claims that are too narrow may be easy to get granted but may offer little real-world value, or misalign with commercial strategy. Overly broad claims, on the other hand, may be quickly challenged or rejected by the patent examiner.

Finding the right balanced scope takes strategic judgment and often several iterations. Solve Intelligence helps streamline this process with claim drafting suggestions, customizable templates, and iterative review functionalities, helping patent teams draft and evaluate strength and coverage of their claims more effectively.

🔗How AI Patent Drafting Software Streamlines IP Protection 

3. Inadequate Disclosure of the Invention

Patent office examiners require a clear and detailed description of how an invention works. If the application lacks sufficient technical detail or leaves out key components, it risks rejection for failing to meet enablement requirements.

This often happens when early drafts are rushed or if the invention isn’t fully documented internally. Companies can benefit from structured intake processes and technology that helps spot areas where the explanation may be lacking or ambiguous. Patent attorneys can use Solve Intelligence’s Patent Copilot to assist in generating accurate, jurisdiction-specific descriptions, as well as leverage Solve Intelligence’s built-in review functionality. 

4. Lack of Internal Consistency and Terminological Clarity

Inconsistent terminology across sections of a patent application can lead to confusion, examiner pushback, or post-grant vulnerabilities. This issue becomes more pronounced in collaborative or multi-author drafts of both invention disclosure material and patent specifications.

Maintaining clarity and uniformity can be simplified with tools that can review and flag inconsistent language or vague phrasing. Solve Intelligence’s Patent Copilot can be leveraged to provide consistent and accurate terminology throughout a patent application.

5. Missing or Misstated Inventorship

Properly identifying inventors is not just a formality. Mistakes here can affect ownership, create legal exposure, or potentially invalidate a patent down the line.

In projects involving multiple contributors or inventors, it's easy to overlook this step or make assumptions. Creating a clear audit trail of contributions, i.e., by documenting and time-stamping R&D activities, helps support accurate patent filings and provides critical evidence in the event of any future legal disputes.

6. Procedural Missteps and Formality Errors

Details matter. Patent filing errors such as missed deadlines, formatting issues, or incorrectly completed forms can lead to unnecessary delays or administrative rejections.

Even when the invention and claims are strong, these oversights can be costly. Compliance can be strengthened by using specialized tools that automate formality checks, generate properly labeled figures, and adapt to jurisdiction-specific requirements. Look for solutions that integrate seamlessly with your team’s preferred drafting workflows to help reduce the risk of administrative oversights.

🔗Best AI Patent Tools for 2025 

7. Poorly Considered Timing

Filing too early can result in an underdeveloped application lacking the necessary technical depth. Filing too late, on the other hand, risks public disclosure that could compromise novelty, or missing critical deadlines related to market launches or competitive positioning.

Having a well-aligned patent timeline—one that takes into account business strategy, product development stages, and disclosure windows—can make a significant difference. Consider building a patent strategy calendar and regularly reviewing it alongside your R&D and commercial teams.

8. Not Coordinating International Filings Properly

Many companies eventually seek patent protection in multiple countries, but international filing requires careful planning. Missteps in timing, translation, or prioritization can limit your global protection or increase costs significantly.

Understanding the Patent Cooperation Treaty (PCT) process, local jurisdiction requirements, and harmonizing claims across borders is key. Establishing a consistent international strategy early on—especially for high-value innovations—helps avoid last-minute scrambles.

Conclusion: Protecting Innovation with Fewer Surprises

Filing a patent is not just about securing protection—it’s about doing so efficiently, strategically, and with minimal risk. These patent application mistakes are common across industries and can be avoided with the right combination of process awareness and supportive technology.

Whether you're managing patent filings in-house or working alongside professionals, putting the right structure in place from the start can help ensure a smoother path to protection.

Solve Intelligence’s Patent Drafting Copilot is purpose-built to support this process—enhancing productivity, quality, and adaptability for in-house legal teams and law firms alike. From multi-jurisdictional compliance and automatic figure generation to customizable templates and prior art integration, our tools are designed to streamline complex drafting tasks and deliver quality applications.

AI for patents.

Be 50%+ more productive. Join thousands of legal professionals around the World using Solve’s Patent Copilot™ for drafting, prosecution, invention harvesting, and more.

Related articles

UK Supreme Court aligns UK software patentability with EPO approach

The UK Supreme Court’s Emotional Perception decision moves UK practice closer to the EPO for computer implemented inventions, including AI. Claims with ordinary hardware will usually avoid the “computer program as such” exclusion, but only technical features can support inventive step. In practice, applicants should focus arguments and evidence on technical contribution and inventive step.

Key takeaways

  1. UK moves closer to EPO, inventive step becomes the main battleground.
  2. Ordinary hardware avoids exclusion, but may not support inventiveness.
  3. Only technical features count at inventive step, not business aims.
  4. Neural networks are treated as software, no special treatment either way.
  5. Draft around technical contribution, measurable effects, and system level impact.

Kicking Off 2026: New Investors, New Customers, New Product Features

A lot has happened in the last two months. We wanted to take a moment to share what we've been building, who's joined us, and where we're headed next.

Since we started Solve, the goal has been simple: help IP teams do their best work by combining real-world patent expertise with deep AI research, intuitive UX, and state-of-the-art security. The momentum we're seeing across the business tells us the market agrees as 400+ IP teams across 6 continents now use Solve.

Here's what's new.

Reflections from AUTM: What Tech Transfer Offices Really Need in 2026

Last week, my colleagues and I attended the annual meeting of AUTM, the global association for technology transfer professionals. For anyone building in the intellectual property (IP) space, it’s one of the most important rooms you can be in.

The three-day conference brings together high education decision-makers from around the world who are shaping how intellectual property is evaluated, protected, and commercialized. This year’s conversations revealed something important: the question is no longer if AI will influence tech transfer, but instead about how institutions will integrate it.

PTAB Case Studies of AI Disclosure Requirements: Part I

Artificial intelligence (AI) is a fast-evolving field with new technical methods, systems, and products constantly being developed. This growth has also been reflected in the dramatic increase in patent filings for AI-related inventions. According to Patents and Artificial Intelligence: A Primer from the Center for Security and Emerging Technology, more than ten times as many AI-related patent applications were published worldwide in 2019 than in 2013, and the increasing trend has only continued since.

Although AI-related patent applications have been on the rise, explicit guidance on patentability requirements have only recently begun to be published by patent offices around the world. Indeed, as a burgeoning field of technology, AI inventions have unique features, such as the importance of training data and the lack of explainability and predictability of trained AI models, that differentiate such innovations from traditional types of computer-implemented inventions (CII). 

These features raise questions about the interpretation of disclosure requirements, among other patentability requirements, for AI-related inventions. For example, how much information, such as source code, training data sets, or machine learning model architectures, should be provided to satisfy the written description and enablement requirements of Title 35 of the U.S. Code § 112(a) or analogs in other patent jurisdictions?

As we await further official guidance from the U.S. Patent & Trademark Office (USPTO) on disclosure requirements for AI-related inventions, we can gather initial indications from recent patent prosecution decisions from the Patent Trial & Appeal Board (PTAB) on such issues. In this article, we study a selection of PTAB appeals decisions for applications for AI-related inventions rejected under § 112. To set the background, we first review a classification of AI inventions and USPTO guidelines on disclosure requirements for computer-implemented inventions. After analyzing three case studies, we conclude with general takeaways and best practices, which emphasize that applicants must disclose specific algorithms and implementation details, not just desired outcomes, to satisfy written description requirements.