If a ( new Ai discovered material ) tree falls in the ( lab ) woods and no one hears it, does it make an ( IP ) sound ? Of course it does.
With the ever increasing space that Ai systems, autonomous agents and integrated Ai code are expanding into, and as recently discussed in MIT Technology Review Ai Materials Discovery Now Needs To Move Into The Real World we are seeing ever increasing situations where Ai is not only validating and extending scientific principals but also where for the 1st time in history, we are seeing situations where specific new breakthroughs are taking place directly due to the output from automated Ai discovery, materials science robotic based experimentation and of course self generative coding systems. The question then is, at the speed and ferocity that these new Ai systems are able to create, and even artistically, build new physical experiments ( in the case of new materials R&D ) having these experiments running in labs is where the value to those that move R&D to production the fastest greater than or less than the patentability of said new breakthroughs?
When automated Ai materials science labs start pumping out scientifically validated materials never seen before and then automatically or with minimal human assistance submitting these efforts for patenting this then begs the question that Ai is automatically or mechanically becoming responsible for the IP protection that goes along with the discovery of new materials ( which may and can be used in enormous quantities ) and this is of enormous value to the firms that are not only using these new materials but also the labs that are producing said Ai augmented if not fully autonomously efforts.
Where we see more and more corporate, government, and large organization groups turning away from Ai as purely a generative and summary engine and onto to a system for unbiased scientific analysis, we see the further exploitation of a method for creating breakthroughs and as directly connected to the triumvirate of innovation: design + R&D + engineering generating IP ( which is protected via legal means ) and then offered to clients of said organization as a defensible part of business operations against external competitors. In modern parlance this is often referred to as the " moat " model of NPD and engineering efforts and as further examined in Evaluating Large Language Models in Scientific Discovery we see the exact value of such a system and process can create for legacy innovation organizations.
Where this then becomes a further power is in the consistent efforts to create and deliver industrial and consumer breakthroughs where the full ( or even partial ) integration of Ai systems into the international IP ecosystem of organizations such as the World Intellectual Property Office - WIPO, the European Union Intellectual Property Office - EUIPO and other such organizations on each of the world's continents takes place. Examples of this are in the power of Ai to limit international trademark trolling, patent infringement, and counterfeit goods similar to the integration of web based, mobile based and block-chain based technologies had similar effects in past technological adoption curves.
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