AI has become firmly embedded in the research and development processes of many companies, enabling teams to automate certain tasks and increase their technical productivity. These benefits are real. Yet the question of AI and intellectual property in R&D is often overlooked. What happens to the inventions arising from these processes? Can they be protected, defended and valorised \u2014 and under what conditions?<\/p>\n
This is the central question that Adrien Marcone<\/strong><\/a>, European and Swiss Patent Attorney and specialist in intellectual property strategy for the digital world (AI\/ML, blockchain, cryptography, IoT) at P&TS, addressed in his presentation on 1 September 2026, at an event organised by CoBooster<\/strong><\/a> in collaboration with Sylvac<\/strong><\/a> and AI Swiss<\/strong><\/a>.<\/p>\n Held at Sylvac<\/strong><\/a>‘s premises in Yverdon-les-Bains, this half-day event brought together more than 40 participants around seven presentations delivered by eight specialists, complemented by two workshops and a guided tour of Sylvac’s facilities. The event was opened by Eric Schnyder, CEO of Sylvac, Jo\u00eblle Tosetti, Managing Director of CoBooster, and St\u00e9phane Fallet, President of AI Swiss<\/strong><\/a>.<\/p>\n CoBooster<\/strong><\/a> is a collaborative platform supporting the creation of project teams, the co-funding of feasibility studies and the transfer of patents within the Swiss industrial ecosystem. P&TS is one of its partners.<\/p>\n Alongside Adrien Marcone, the following speakers took part:<\/p>\n In his presentation, Adrien Marcone identified four issues that any company risks facing when deploying AI in its R&D processes without having first defined a solid intellectual property framework. These situations are relevant to both technical teams and legal departments, regardless of the size or sector of the organisation.<\/p>\n Submitting R&D data to third-party AI tools directly exposes a company’s trade secrets and confidential information. The risk takes on a particular dimension from a patent perspective: even partial disclosure of an invention prior to filing a protection application can definitively compromise any prospect of patent protection.<\/p>\n To manage this risk, it is essential to:<\/p>\n Under the law, AI cannot be designated as inventor or author. It is the human contribution \u2014 documented and traceable \u2014 that determines any possibility of claiming ownership.<\/p>\n To secure ownership of inventions, we recommend:<\/p>\n The outputs of an AI system tend to approximate the state of the art, which increases the risk of inadvertently infringing existing patents. There is also a methodological difficulty: AI is not always a reliable tool for assessing the state of the art in patent matters.<\/p>\n To manage this risk:<\/p>\n AI code-generation tools have been trained on codebases covering a wide range of licences, including copyleft licences (GPL, LGPL…). Code subject to such obligations may inadvertently become incorporated into a proprietary codebase. In the worst-case scenario, a company may be legally required to release its entire codebase as open source.<\/p>\n To prevent this, it is important to:<\/p>\n In summarising his presentation, Adrien Marcone put forward three principles that capture the issues developed throughout his talk:<\/p>\n These three principles are not solely relevant to large companies with dedicated legal departments. They apply to any organisation that innovates with AI, regardless of size or sector, and that wishes to be in a position to protect, defend and valorise what it creates.<\/p>\n It is precisely to address these challenges that P&TS has developed, within a team of complementary technical and legal profiles, solid expertise in the field of IT and AI law<\/strong><\/a>, serving the companies and academic institutions that innovate in the digital world.<\/p>\n Photos: @CoBooster & P&TS<\/strong><\/p>\n\n\t\tAn Event Dedicated to the Industrial Practice of AI in R&D<\/strong><\/h2>\n
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Four Intellectual Property Considerations to Anticipate When Using AI in R&D<\/strong><\/h2>\n
1. Your R&D Secrets May Already Be Exposed<\/h3>\n
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2. AI Created It. But Who Owns It?<\/h3>\n
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3. Your AI Outputs May Infringe Existing Rights<\/h3>\n
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4. Free Code, Costly Consequences<\/h3>\n
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Three Guiding Principles for Protecting What AI Contributes to Creating<\/strong><\/h2>\n
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