In this exclusive interview, we are honoured to speak with Dr. Coreena Brinck, a seasoned Chartered (UK) and European patent attorney with over two decades of experience. Dr. Brinck's career has been devoted to pioneering computer-implemented inventions, especially within the rapidly evolving field of artificial intelligence. Her expertise spans a vast range of sectors, from communications to automotive, energy management, and beyond. With her unique perspective as Head of IP at IntuiCell—a groundbreaking AGI startup out of Lund University—and as a consultant at The Brinck Consultancy and Two-IP, Dr. Brinck offers invaluable insights into the challenges and opportunities facing IP professionals in the age of AI. As Chair of Day 1 at London IP Week this December, she will bring her expertise to bear on discussions of AI’s transformative impact on the IP landscape.
In our conversation, Dr. Brinck delves into the most significant trends shaping the future of IP, the evolving role of AI tools, and her perspectives on how IP professionals can navigate the complexities of this unprecedented era. Enjoy the interview!
What do you see as the most significant global trends and challenges currently impacting the IP landscape, and how should IP professionals prepare to address these issues?
Firstly, I have to say that whilst most media coverage has focused on the rapid development of LLMs (large-language models), this type of AI has fundamental limitations. Various research groups around the world, including the team I work with in Lund, are developing new types of AI to address these limitations. Despite their long-term limitations, LLMs are now ubiquitous, and many LLM-based models are being used to develop IP tools across areas like searching, drafting, prosecution, and portfolio management.
As professionals—whether in-house or in private practice—it’s increasingly important to be aware of the types of tools being developed, how they work (e.g., how prompt-screening is handled, sandboxing status), and the confidentiality of the information you provide to these tools. While these tools will allow us to improve workflows, quality, and efficiency, expectations around time-efficiency should remain moderate, as these tools are not perfect and have limitations. I encourage IP professionals to be curious, explore these tools, and determine for themselves how they can enhance their practice.
There are already AI legal tools that can help search for and in prior art documents to find relevant sections of interest, point out differences between one document and another, generate summary statements from claims (and even full descriptions), check for parts and element matching, generate flowcharts from method claims, draft a response to an office action, and much more. However, while many tools can technically draft an entire application from an invention report—and the results may look like an application to non-professionals—and while these may even be sufficient for some very basic inventions, the reality is they cannot perform claim drafting the way a patent attorney will. What they can do are some amazing things to help you save time you can then spend drafting a great set of claims.
The main thing for IP professionals is to learn how to use these tools effectively, to understand and recognize their limitations, to develop ways of working that raise the bar for quality and increase time efficiency, and to remain accountable as an IP professional for the quality of work—regardless of whether it is our hands, a human technical assistant’s hands, tapping on a keyboard, or an LLM that generated it.
With your background in physics and experience in the IP world, how do you think scientific and technological advancements are shaping the future of patent law and enforcement?
Advances in sectors such as AI and quantum computing (QC), will continue to influence the development of a wide range of technology sectors. Patent law is likely to evolve with increased litigation in areas such as:Â
i) Plausibility: As both AI and QC are developing rapidly, there can be big jumps between how an invention is implemented and published prior art, and some inventions are fairly complex systems. This means there is a greater likelihood that patent descriptions may not provide a plausibly enabling disclosure over the whole scope of the claimed invention.
ii) Joint Infringement:Â Recognising the most likely commercial deployments to target single-actor method claims can be very challenging, particularly when there are distribution chains involving multiple parties, especially when working with more academic material from inventors who may only have vague notions of what they will be doing commercially when the application is being drafted.
iii) Human Inventorship: DABUS inventor-type issues will continue to haunt computer-implemented inventions, particularly AI and QC, as more and more code gets generated by a computer rather than a human programmer.
iv) Standards and Licensing: There can be tensions between drafting claims to target the smallest infringeable unit and claims to maximise effective control and boost licensing revenue in a particular context of use of an invention. We are seeing this sort of tension coming through already, for example, in the automotive sector for communications technology.
How do you think the introduction of the UPC will change the way companies approach patent disputes, especially in fast-evolving areas such as AI and digital innovation?
Realistically, I think the UPC will become the favored forum for many disputes due to its larger territory for direct infringement. Even though AI and digital innovation are fast-moving, meaning there is a higher chance prior art may be missed during prosecution and brought to light only during litigation, a UPC win is likely to outweigh the risk of losing a patent to such prior art.
AI and machine learning are often described as disruptive technologies. From your perspective, how are these technologies influencing the IP landscape, especially in terms of patent eligibility and protection for AI inventions?
A major area is digital copyright, where right now it feels like we have returned to the nascent era of bootlegged music downloads, when many individual musicians and the music industry as a whole had to fight for the right to protect their livelihoods by battling illicit copying and downloading. I am surprised that just because it is an AI-bot scraping someone's copyrighted work off the internet for training an AI system, some people think it is okay— it is NOT "okay" in my opinion. I think this is a rampant copyright breach unless the consent of the copyright owner for the use of their work to train an AI system is obtained.
Another influential area will be inventorship, as more code is automatically generated by AI systems. There will be a lot of exploration around what subject matter is eligible for core AI, where the models themselves are fundamentally new and inventive. Computer-implemented inventions are patentable only if the claims are not directed to excluded subject matter. So even if a claim may be novel and inventive, it may not be eligible subject matter for patent protection in some or all countries.I will also say in passing that keeping up with the latest EPO guidelines, UKIPO practice, and the practices and patent law of the USPTOÂ and other patent offices around the world is incredibly important for patent professionals working with CII technology, so that the CII claims we draft are eligible for patent protection in different countries with a reasonable chance of success. This is, by the way, one area where I always recommend using a human patent attorney!
How do you see AI being integrated into legal processes, from patent reviews to IP litigation, and where do you see the most potential for innovation in the next decade?
From an innovation standpoint, I believe AI will be integrated across all areas of legal processes. The greatest potential lies in IP licensing and litigation, with more sophisticated tools for identifying infringement, licensing opportunities (especially in standards contexts), and generating reliable evidence to challenge patent validity through locating prior art and addressing added-subject matter.
Dr. Coreena Brinck’s deep knowledge of AI and her forward-thinking perspective on the IP landscape provide invaluable guidance for anyone working in intellectual property today. Her insights into emerging trends, AI-driven tools, and best practices for navigating the future of patent law underscore just how pivotal AI will be in reshaping the industry.
Don’t miss the chance to hear directly from Dr. Brinck and other leading experts as they explore these critical topics at London IP Week this December. Join us for an engaging and informative two-day conference that promises to equip you with the knowledge and tools to thrive in the evolving IP landscape.
Interview : Phoebe Simpson | Editor : Chi Nguyen | Graphic Designer :Â Ssozi Arthur Grace
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