IP planning is key to protect AI innovations
6 June 2025
This article was written for Digital Forge, a membership-based organisation that runs events in the North of England for investors, entrepreneurs across tech and manufacturing sectors. Learn more about Digital Forge from their website – forgedforgrowth.com
Much has been published about the role of AI in innovation, but still relatively little has been said about the role of intellectual property (IP) in protecting AI-based systems and algorithms. Without some knowledge of how to construct an IP portfolio however, SME innovators could miss out on investment opportunities and leave the way open for competitors to copy their key innovations.
Much like those in any other fast-moving area of R&D, innovators of AI and machine learning-related technologies often have to invest large sums at an early stage. This money is spent in developing and training models, and then testing their deployment for specific end uses or applications. Securing patent protection at the outset will not only prevent competitors from copying their innovations and potentially winning the race to market, it can also help to attract investors seeking to capitalise on a growth market.
The Government’s UK AI Opportunities Action Plan, published at the start of the year, aims to ensure that Britain doesn’t fall behind in the global race for AI. With new AI Growth Zones being established and a commitment to expand sovereign compute capacity and make public and private datasets more widely available for AI training, the domestic AI innovation curve is expected to rise sharply. At a time of rapid market expansion, it is more important than ever that SME innovators seek advice about protecting and commercialising their AI or machine learning innovations at an early stage.
The benefits of IP planning are well documented – investors will typically look for a strong IP portfolio, seeing it as an indication that there is value in the business. They are more likely to be drawn to investment opportunities if high-quality patents exist covering the business’ core activities. As an example of this within the AI and machine learning space, Featurespace, a company specialising in financial fraud detection has around 100 patent filings and was acquired by Visa in 2024 for a reported £700m. Similarly, Tractable, an innovation-led company that uses next generation AI to visually assess damage caused to property or vehicles, owns 35 patent filings, and has successfully raised a total of $185m over seven funding rounds.
Research compiled recently by European intellectual property firm, Withers & Rogers, shows that while around two thirds of European patent applications for AI inventions relate to the use of existing algorithms to solve a technical problem, a growing number are directed to the algorithms themselves. The research reveals that about one in four relate to AI and machine learning algorithms. A similar picture is evident in other parts of the world, for example, in the US.
The public nature of patent applications requires careful consideration. Every patent application will publish, typically 18 months after filing, unless withdrawn prior to publication. Innovative businesses therefore need to weigh up which aspects of their activity to put forward as patent applications and which are best kept as trade secrets. One key question underlying this consideration is how easy it is to detect infringement. If a company cannot identify when an infringement has taken place, it is difficult to enforce their patent rights and stop competitors from copying them. However, without patent protection, there is always a risk that a competitor might develop something similar and secure a monopoly to bring it to market. Therefore, it is important for companies to discuss and develop a robust IP strategy as early as possible in order to ensure that their core innovations are suitably protected and their value captured.
The number of international patent families focused on core AI technologies has been increasing at an average rate of 54.6% since 2010, according to data released by WIPO. As a result, patent offices around the world have gained considerable knowledge about AI and its role in innovation, which is helping to smooth the way for SME innovators. The European Patent Office (EPO) recently published its ‘New Guidelines for Examination’, which make it clear that as long as innovators can demonstrate that their invention provides a technical solution to a technical problem, it will be assessed and examined in the same way as other software-based inventions. Other patent offices, such as those in the UK, the US and Japan, have also released useful guidance explaining how AI and machine learning based patent applications are examined.
In a rapidly evolving space, it is still possible for inventors of AI and machine learning-enabled technologies, even those making use of recent GenAI advances, to stake a claim to the emerging market opportunity. They can do this either by bringing solutions to market with the protection of monopoly rights or by licensing their innovations to third parties in exchange for royalty payments. Both options will involve building a robust, multi-dimensional patent portfolio and IP strategy that is built on an understanding of its commercial strengths.
Harry Strange
Electronics, Computing & Physics group
This publication is a general summary of the law. It should not replace legal advice tailored to your specific circumstances.
© Withers & Rogers LLP June 2025
