Steinbeis experts provide free training on how to use AI for synthetic inventing.
The advent of generative AI is revolutionizing the intellectual property (IP) and innovation landscape. Synthetic inventing is playing an increasingly important role in the development of valuable patent portfolios, especially for small and medium-sized enterprises. Generative AI is reshaping traditional patent value chains and innovation processes. This is having transformative impacts on patent strategies and patent management and is creating both opportunities and challenges for businesses. The Center for International Intellectual Property Studies (CEIPI) carried out a case study to investigate the impacts of AI-assisted inventing. Meanwhile, the Steinbeis Transfer Institute for Intellectual Property Management provides free training courses from the joint program with the European Patent Office on how to use AI for synthetic inventing. The funded training courses are now being extended to the chemical industry.
The comprehensive case study carried out by the Center for International Intellectual Property Studies investigated the use of AI in the invention process. An AI-assisted “white space analysis” that allows researchers to systematically identify potential innovation areas that are not yet heavily patented formed a key part of the study.
The patentbutler.AI tool was used to carry out the white space analysis of the patent landscape. The process began by defining the initial features of the desired patent. This allowed patents with similar features within a chosen portfolio to be identified and similarities to be analyzed based on individual features or combinations of features. The iterative changing of features then enabled the identification of areas that are not well covered by existing patents.
The study showed how AI can generate inventive solutions based on known innovation principles. For instance, researchers used AI to apply TRIZ (Theory of Inventive Problem Solving) principles to a smart parking use case. The AI generated several inventive solutions that used different TRIZ principles, demonstrating how AI can enhance and accelerate the invention process.
Synthetic inventions in patent portfolios
The case study shows the growing importance of synthetic inventions in the development of valuable patent portfolios, especially for small and medium-sized enterprises. Synthetic inventing uses white space analyses to systematically identify inventions in the desired areas. Patent applications are drafted based on these inventions. This approach allows companies to create spheres of exclusivity as part of a 360° IP strategy, to systematically identify IP needs, to focus on competitive effects rather than solely on technical features, and to develop patents that are closely aligned with strategic business objectives.
Training programs for AI-assisted inventing
In order to support the introduction of AI-assisted invention processes, the experts from the Steinbeis Transfer Institute for Intellectual Property Management have developed and delivered training programs for different industries. The programs aim to equip SMEs with the skills and knowledge to use AI in their innovation processes, to develop patent strategies, and to build their own patent portfolios.
“The training programs support development processes in companies through the use of AI. We show how to get popular generative AI applications to use creativity techniques and generate ideas for concrete development problems”, says Steinbeis Entrepreneur Professor Dr. Alexander J. Wurzer. The training also explains how both popular and professional AI applications can be used to differentiate the AI-generated development ideas from the known state of the art.
AI in the chemical and pharmaceutical industry
Different AI systems are increasingly being used in the chemical and pharmaceutical industry and for patent portfolio development. AI methods like Generative Adversarial Networks (GANs) and Reinforcement Learning (RL) are being employed at various stages of the drug discovery process and in the development of chemical compounds. Some of the most important applications include protein structure prediction, screening, compound property prediction and the creation of new chemical compounds.
As well as speeding up the innovation process, the use of AI in the chemical and pharmaceutical industry also creates new challenges and opportunities with regard to patent strategy. Companies in this sector are increasingly recognizing the need to adapt their IP strategies to factor in AI-generated inventions. As a result, the Steinbeis experts are now also offering their free training program to chemical and pharmaceutical companies.
Alexander J. Wurzer underlines the importance of AI-assisted inventions: “The CEIPI case study demonstrates the potential of AI-assisted inventions and white space analyses in identifying new areas for patents. The growing use of synthetic inventing, especially among small and medium-sized enterprises, has created a need for strategic approaches to patent portfolio development.” As AI continues to evolve, its impact on a range of sectors, from the software to the chemical and pharmaceutical industry, will become even greater. Training programs and modified IP strategies will be vital to making effective and efficient use of the available tools.
You can find further information and register for the free training here:
Contact
Prof. Dr. Alexander J. Wurzer (author)
Steinbeis Entrepreneur
Steinbeis Transfer Institute for Intellectual Property Management (Gauting)
Dr. Laura Fè (author)
European Patent Attorney
www.murgitroyd.com
227255-49