Five Ways AI Can Help with IP Portfolio Management

3D Render of an Android searching documents

There is no question that artificial intelligence (AI) has led to a monumental shift in intellectual property law and strategy. Most companies and attorneys are familiar with the current unsettled legal landscape as it relates to inventorship laws for intellectual property—namely, that inventions and works that are created through AI may or may not be eligible for patent or copyright protection, depending on the circumstances. But quietly in the background, AI has already been changing—and continues to change—how IP portfolios are created and managed. Below are five key ways that AI is changing how companies handle their IP portfolios. 

1. Simplifying Prior Art Searching

Any company with a patent portfolio frequently has the need to understand the prior art landscape. Whether it is to evaluate whether a new product is patentable, assess risks relating to a competitor’s portfolio, or respond to claims of infringement, companies (and the law firms that represent them) frequently need to understand prior art in a particular area. Often, this information is needed quickly to respond to ongoing business or legal issues.

As most lawyers know, a wealth of prior art search firms have developed across the globe and can be engaged to perform a prior art search. But AI technology has begun to disrupt this practice, allowing counsel and companies to bring those searches in-house. AI allows prior art search results even more quickly and easily than ever before. For example, Relativity (well known for its document review platform) has created Relativity Patents, a platform that harnesses the power of AI to perform prior art searching simply by entering an existing patent number or a few key words.

Even the U.S. Patent and Trademark Office (USPTO) has jumped on board with AI for prior art searching. It has developed an AI tool for examiners to conduct prior art searches, designed to improve the accuracy and efficiency for examiners who must comb through mountains of prior art in reviewing applications.

In short, AI has changed the face of prior art searching, whether in the context of applying for patents or defending against infringement claims.

2. Preparation of Patent Applications

It is no surprise that inventors have begun to experiment with the use of AI in drafting patent claims and applications. There are various companies with AI technology that claim to automate certain functions of patent drafting. And, of course, you can ask ChatGPT to draft a patent application.  But while it may be a tempting proposition for an inventor to save time and costs by using AI to draft a patent application, there are concerns that may outweigh any efficiencies achieved. As a preliminary matter, ChatGPT is not confidential, so using it could trigger time bar limits that might not exist otherwise. Additionally, the quality of any application generated by AI should be thoroughly vetted by an attorney prior to submission, which may negate any initial time or cost savings (or potentially create even more work). Most practitioners have heard now about AI creating false citations in a legal brief. The same concerns are present when using AI for the drafting of a patent application. Serious caution should be exercised if you are utilizing AI to draft a patent application.

3. Improving Trademark Enforcement Capability

AI is discussed somewhat less frequently in the trademark context, as trademark law does not have the same inventor/author requirements as in patent and copyright law. Nonetheless, AI has permeated the world of trademarks as well. Companies and their counsel have for years used AI to aid in monitoring for potential infringement and counterfeit products. To conduct this process manually is very labor-intensive, given the plethora of online sellers, websites, and social media where unauthorized sellers abound. AI is well suited to managing the task of reviewing postings and identifying trademark infringement in significantly less time than it would take a human. The use of AI to monitor trademark infringement has freed up personnel to focus their efforts on other tasks relating to enforcement of the trademarks, making the entire process more efficient and effective.

4. Aiding Trademark Prosecution and Examination

AI has also permeated trademark law through its use in evaluating potential marks. Numerous jurisdictions are developing AI programs to assist trademark applicants and examiners in assessing existing marks, including the United States, Australia, China, and the EU. The World Intellectual Property Organization (WIPO) has identified dozens of such initiatives in the trademark space.  These AI programs include search functions for applicants for both word and image marks, again turning what was once a labor-intensive manual process into a quicker, more efficient search of current registrations. The ability to assess relevant marks more quickly saves companies time and money in their brand protection strategy.

5. Supporting Strategic Patent Portfolio Management

AI can also be used to assist in portfolio management. Effectively managing a portfolio requires the often labor-intensive process of assessing the substance of a patent portfolio, evaluating areas of coverage, determining which areas have weaker coverage, and potentially comparing a company’s portfolio to that of its competitors. In addition, companies may want to value a patent portfolio as whole, or the individual patents within it, whether for purposes of “pruning” a portfolio and determining which patents are worthy of continued maintenance and which are not, or in considering the value of a potential acquisition target. Conducting this process with hundreds or thousands of patents can be extremely arduous. There are products offered that promote the use of AI to value and even rank patents based on their importance to the company. These types of AI tools, while not a complete replacement for business strategic assessments, can significantly reduce the amount of human labor required to make such assessments, allowing businesses to focus on their strategic goals in a more efficient and organized manner.

Don’t Be Left Behind

AI has already made numerous changes in how IP portfolios are created and managed. Although AI cannot fully undertake strategic management of an IP portfolio, many of the current AI tools can maximize a company’s efficiency in creating and maintaining its portfolio. Companies should continue to stay up-to-date on the latest technology advances in this field and consider how it may help their businesses moving forward.