The rapid evolution of AI is reshaping creativity, innovation and the business activities tied to them, promising potential for streamlining processes, eliminating redundancy and accelerating the pace of innovation write Maaike van Velzen, partner Intellectual Property and Tech law at Deloitte, and Julian Nolan, CEO and founder of Iprova
The rapid evolution of AI is reshaping creativity, innovation and the business activities tied to them. AI enhances every stage of the innovation process, including strategy, IP management, product design and marketing.
One significant impact is on the very act of innovation – creating future inventions and foundational patent portfolios.
While AI is a useful addition for driving innovation, the business value of innovation is usually embodied in the value of the resulting intangibles, such as intellectual property rights. Rights like patents are granted after a thorough examination process, which may be influenced by AI technologies.
Furthermore, the legal context of innovation through AI usage is created by regulations on re-use of data, privacy laws, ownership clauses in contracts and regulations like copyright law.
Thus, the influence of AI on innovation and IP is a multidimensional web, with societal, technical, economic, environmental and political threads weaving together to create a complex tapestry.
AI presents both opportunities and challenges for Chief Intellectual Property Officers (CIPOs) and General Counsels (GCs). While it boosts innovation and addresses complex issues like climate change and health, it also raises concerns over job security, privacy and ethical use of data.
The evolving EU legislation, including the AI Act, Digital Services Act (DSA) and Digital Markets Act (DMA), focuses on responsible data use and sets the stage for IP rights associated with AI-generated outputs.
CIPOs must navigate these regulations together with the GC and legal team to safeguard IP while leveraging AI’s transformative potential responsibly. This overlay of roles across CTO/CIPO and GC has already been initiated but requires acceleration and strong team-up to address AI appropriately in a company.
Figure 1: AI is impacting every stage of the innovation process, from strategy/foresight through to IP portfolio management, through to product design and market testing and ultimately marketing.
The current surge in AI-generated inventions could overwhelm patent examination processes with questionable prior art and numerous auto-generated publications. CIPOs and CTOs must guide innovation and IP teams on AI-generated prior art.
AI holds promising potential for streamlining processes, eliminating redundancy and accelerating the pace of innovation. It promises a move away from the traditional, more cumbersome ‘trial and error’ approach towards a more streamlined, directed innovation pathway. This creates efficiency and productivity, with reduced costs and faster time to market, reducing dependency on a brilliant thought from an inventor.
Perspectives on AI, innovation and IP
We now touch on various perspectives in a non-exhaustive description on innovation and IP that can trigger the CIPO, CTO and GC to adapt to new ways of working.
Perspective one: From ownership to risk management
In the mid-term, the focus is likely to concentrate on ownership issues related to AI-generated IP. Discussions around patent inventorship and copyright for new creative works generated by AI are likely to dominate legal and policy debates for some time to come.
In parallel we see attention increasing for the risk perspective on the use of data and other input, such as pictures, for learning and training AI systems.
The CIPOs position, between technical and legal viewpoints, must address risk and opportunity with CTO and GC.
Perspective two: Creating inventions at lower cost
In the long-term, we can expect a paradigm shift in the pace and nature of innovation. The ability to create inventions at a lower marginal cost through AI may trigger a reconsideration of patent strategy. The focus might shift from merely protecting inventions through patents to a more open strategy of publishing, lead-time through inventiveness, and pre-empting competition.
CIPOs must understand how this affects portfolio value. Lower invention cost and enhanced speed may emphasise brand and design specifically in consumer goods. Luckily most CIPOs nowadays guard all types of IP, for those who do not it is highly recommended to align with the trademark and design team.
Perspective three: There are many considerations if AI is to generate useful results
Data is crucial for AI training and evaluation, with its quality, quantity, and diversity affecting AI performance. Data use involves navigating privacy concerns, regulatory hurdles, and ethical issues.
Bias in AI, often from unrepresentative training data, is a major concern. Broad and diverse data training is necessary for versatility. Data retention regulations further complicate AI’s ability to reproduce outcomes. For the CIPO, this means having a broad network across CTO, CFO and GC in the organisation to ensure that all relevant aspects of AI are appropriately addressed.
Figure 2: Two long-term scenarios: a world where invention creation is simplified and speed is enhanced and a world of democratised invention generation where creations are primarily published rather than patented
Scenarios: imagining the extremes
We imagine two extreme scenarios for the long-term future. One is a world where invention creation is simplified and speed is enhanced, leading to an explosion of patents: the world of patent bubbles and data pools. The other is a world of democratised invention generation where creations are primarily published rather than patented – a scenario that could radically transform the current understanding and practice of IP rights and protection: the world of publishing and sharing. Characteristics of these worlds vary widely (see figure 2 above).
Navigating the future with foresight
As we stand with one foot over the threshold of an AI-driven future, the roles and responsibilities of various stakeholders are crucial. Companies, patent offices, users, policy makers and educational institutions must prepare to navigate this new landscape.
This includes managing input data use, adapting to an evolving job market, integrating AI training into education and anticipating shifts in societal norms and regulations.
CIPOs and IP teams should define policies on IP generation and whether a more open approach to data and IP or a more closed one suits their businesses’ goals. We must also consider what we would suggest the European Patent Office or other patent granting agencies, policy makers and educational institutions to do in this changing landscape.
These stakeholders should drive efficiency, adapt patent office regulations to accommodate AI, integrate AI into education and manage potential HR disruptions particularly in R&D and IP teams.
The patent system is becoming more integrated and intertwined with other regulations such as the AI Act, data privacy and more. CIPOs will need to look into how acts like DSA, DMA, AI Act, GDPR, DORA and many others are aligned with traditional IP regulations.
Obligations arising from one act may impact the results of another, for example related to publication and transparency requirements in the AI Act and confidentiality before patent filing.
We are at the beginning of an era where AI may not change the act of invention making but will undoubtedly transform how we use tech and tools to create and innovate and how we distribute ownership and access to innovation in fair, sustainable business models.
With thoughtful consideration, strategic planning and responsible execution, the era of AI-assisted invention promises exciting possibilities for creativity and innovation to address significant societal challenges.