Originally posted on IPKat.
Indeed, many partners freely admit their intention for trainees or recently qualified attorneys to never be given access to AI tools for patent work, arguing that the skills of the patent profession must be forged manually through hard graft.
On the face of it, restricting the use of AI for patent work to the most experienced patent attorneys makes sense. After all, how is a trainee to learn the skills of the trade if they can simply rely on AI from day one? Furthermore, given that AI tools also need considerable input and direction from a qualified attorney in order to produce an acceptable output, giving AI to trainees is unlikely to produce satisfactory outputs. On the other hand, this approach potentially creates serious problems for the profession, including slowing (or even halting completely) AI adoption, whilst simultaneously encouraging risky AI shadow use.
The risks of shadow use
In our view, a likely and potentially very serious consequence of demanding that the newer members of the profession refrain from all AI for professional work, is shadow use. Blocking access to every available model is probably a technical impossibility for IT departments. After all, if access to the major platforms is restricted, individuals may simply pivot to using one of the many alternative Large Language Models (LLMs), such as Mistral, DeepSeek and Grok, to name but a few.
Any shadow AI use by attorneys in a firm is, of course, highly problematic. First, such use is generally going to be via personal accounts rather than secure enterprise platforms. Outside of enterprise commercial versions, the foundational LLM providers by default retain the data inputted into these public accounts to train and update their models. The inputs are therefore not considered confidential (Evolve Insights). This means that any sensitive information fed into the prompt could equate to public disclosure. Feeding client confidential data into these systems is likely to constitute a severe breach of confidentiality. Even if the shadow user attempts to avoid inputting direct client confidential data, the security risks are huge. The problem simply cannot be ignored.
Gatekeeping the future: The proud dinosaur dilemma
Added to the risk of shadow use is the problem that restricting access to AI systems is likely to hinder AI adoption and development within a firm. We suspect that restricting AI usage to only the partners within a firm, in many cases, may mask an underlying reluctance for AI adoption. Senior members of a firm may have little incentive to embrace new technology that might threaten the traditional revenue stream of the firm, based as it is on the billable hour (Evolve Insights). After all, many of the “proud dinosaurs” freely admit they are simply hoping to retire before they are forced to adapt. These attorneys are the ones who will regale you with a humorous anecdote about a severe hallucination they experienced a couple of years ago. After trying an AI-wrapper for patent drafting, they insist the technology is simply not ready.
By contrast, the younger members of the profession are uniquely positioned to assess and improve AI systems. Scientists entering the field from university or industry will now probably be native users of the technology who use it all the time for many tasks. We can quite imagine their consternation when they enter the patent profession and are told that they must abandon all use of AI.
Limiting AI use to only the senior attorneys (many of whom will have very clear ideas of how things should be done, and why the old ways are best), is unlikely to be the best way of assessing all of the potential value of the software. Meanwhile, the individuals probably most adept at prompting and workflow optimisation are left unutilised and unable to share their knowledge (Evolve Insights).
In this context, the greatest barrier to AI adoption within the patent industry, as we see it, is the general lack of appreciation in the profession of what these tools are capable of, when the effort is put in to use them properly (Evolve Insights). Just as new trainees add value with their recent direct experience of the science, they can also teach the more mature members of the profession how AI can be used.
Corporate vulnerabilities
Of course, companies and clients face an identical AI crisis to patent firms. Worse still, corporate employees are often far less aware of the risks associated with inputting confidential information into personal AI accounts lacking enterprise-grade security guardrails. If a researcher inputs a new antibody sequence or chemical structure into a public chat interface, they risk this information being considered a public disclosure and potentially invalidating a future patent. In-house IP departments therefore have an important role in educating company employees about the risks of AI use outside of the confidentiality guardrails. Using these systems is just too easy.
Of course, the most effective solution to this problem would be to provide enterprise-grade access across the organisation. However, this can be prohibitively expensive. Companies must weigh up the financial costs of enterprise-grade AI for everyone, versus the risks of inevitable shadow use in its absence. Whatever decision is made, a comprehensive AI policy and practical AI training are essential. Patent attorneys should now be equipped with the knowledge to advise their clients on this issue. This means understanding the difference in confidentiality provisions between personal accounts and those with enterprise-grade security, the different levels of confidentiality available between different enterprise accounts, the confidentiality and security risks of AI-wrapper software and how to assess this, the data storage provisions of the AI tools you and your clients are using and how this may affect legal privilege and discovery during litigation, and what workflows are in place to validate AI outputs.
Analysis
The profession cannot afford to bury its head in the sand when it comes to AI. In our view, banning the technology outright will only push its use into the shadows where the greatest dangers lie. Even ignoring these risks, not allowing the new entrants to the profession to use and help develop the AI tools employed within a firm will severely hamper AI adoption.
The problem faced by patent firms is similar to that of universities. Some universities have an outright ban on the use of AI by students, whilst others require its use. As readers might suspect, we are all in favour of giving everyone access to AI, and sees no reason why this should be an impediment to effective learning or training. Every work-product will still need review and sign-off by a qualified attorney. Given how much we still need the human-in-the-loop when it comes to the use of AI in patent work, trainees using AI who do not know the IP law will not produce something that will pass muster. Using AI will simply speed up the process of generating their first draft, and may even be an effective education tool. As with all AI usage in the patent industry, the key is knowing how to use these tools effectively.
Author: Rose Hughes
Rose is a biotech and pharmaceutical patent specialist with over a decade of experience in intellectual property. Rose is a patent attorney at Evolve, where she leverages our unique fractional in-house model to provide clients with deep patent law expertise combined with the strategic commercial oversight typically associated with senior in-house counsel.
With a PhD in Immunology from UCL, Rose applies her technical background to complex innovations in biologics, cell and gene therapies, and the rapidly emerging field of AI-assisted drug development. Previously, Rose held the role of Director. Patents at AstraZeneca, where she was responsible for global IP portfolios and IP strategy at every stage of the pharmaceutical pipeline, from platform development and on-market commercialization to SPCs and patent term extensions.
A recognized thought leader in the field, Rose has been a regular contributor to IPKat since 2018, offering practical insights into European patent law developments. She is also a frequent speaker on the epi podcast, a guest lecturer for the Brunel University IP law Postgrad Certificate, and a contributing author to published books A User’s Guide to Intellectual Property in Life Sciences (2021) and Developments and Directions in Intellectual Property Law (2023).
