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The word "patent" is derived from Latin and means something like open and freely accessible. It was only in the course of the various waves of the industrial revolution that the term took on its current meaning as a property right. The digital revolution also presents patent law with innovations. This involves very fundamental questions such as: What is an innovation anyway? And who creates it so that it can be protected?
AI in the innovation process: not "what", but "how"
Artificial intelligence is playing an increasingly central role in the innovation process of companies because it is no longer merely supportive, but is changing the way innovation is created. First of all, it helps companies to identify new opportunities by analysing large amounts of market, customer and technology data and making patterns visible that would be almost impossible for humans to recognise on their own. This allows trends to be identified earlier and innovation decisions to be made on the basis of data rather than relying primarily on intuition.
In addition, AI itself becomes part of the creative process. As a co-creator, it supports the development of products, services or business models, for example through generative designs, rapid prototypes or the generation of numerous variants in a short space of time. This accelerates iterations, reduces the costs of experiments and enables teams to work more boldly and exploratively. As a result, innovation is less linear and more in loops of trial and error and learning.
Another important role of AI lies in increasing the efficiency and scaling of innovation. Automation, simulations and optimisations can shorten development and test phases, reduce risks and accelerate market launch. At the same time, AI enables a deeper understanding of customers as it continuously evaluates feedback, recognises behavioural patterns and supports personalised offers. Innovation is thus more closely aligned with actual needs and loses the character of a purely "top-down design".
At a strategic level, AI ultimately acts as a catalyst, forcing companies to fundamentally scrutinise their understanding of innovation. It influences which competences will be decisive in the future, which business models will remain viable and where new added value will be created. It is important to note that AI does not replace innovation: without clear goals, good data, human judgement and ethical and legal guidelines, it can even reinforce existing errors in thinking. However, when properly embedded, AI becomes a central factor that makes innovation continuous, faster and more effective.
What counts as innovation? The "why" and "what for" in the hybrid process
AI does not produce innovations in the human sense. It has no goal of its own, no need for novelty and no understanding of meaning or context. What it does is recognise patterns in existing data and reassemble these patterns into something new. In this sense, AI is always based on what already exists - on previous ideas, solutions, designs or texts.
However, this also applies to a lesser extent to human innovation. Hardly anything is created radically "out of nothing". Many ground-breaking innovations are also recombinatory: familiar elements are brought together in a new context, in a new combination or with a new objective. The difference is less the what than the why and wherefore.
It can be deduced from this that AI recombines systematically, quickly and in a large space of possibilities that humans alone cannot survey. This results in combinations that humans would either have thought of very late or not at all. In technical areas such as materials research, drug development or product design, this can lead to results that are objectively new and functionally superior - even if they can be logically derived from existing knowledge.
What AI lacks, however, is the intentional-innovative moment:
It does not recognise itself which problem is relevant.
It cannot assess why something is socially, culturally or strategically significant.
It does not take responsibility for breaking with existing paradigms.
This is why innovation is almost always hybrid in practice: humans set the direction, meaning and evaluation - AI expands the search space, accelerates variation and reduces the costs of failure. Of course, this also harbours the risk of misuse, as AI itself can only question the values and ethical framework on which its tasks are based from the logic programmed into it.
The significance for patent law
Artificial intelligence poses profound challenges for patent law because its basic logic has historically been centred on human inventorship, traceable creative achievements and clearly definable technical teachings. AI-supported innovation processes are increasingly breaking through these assumptions and creating legal tensions in several key areas. Here is an overview of the challenges:
Inventorship:
Under current patent law, only natural persons can be considered inventors, while AI is legally considered a tool. In practice, however, it is often unclear to whom an AI-supported invention should be attributed. This results in the following problems in particular
lack of recognition of the actual role of AI in the invention process
Uncertainty in the attribution to developers, operators or users
legal constructions that are technically imprecise but pragmatic
Inventive step:
Patent law requires an invention to be non-obvious to a person skilled in the art. However, AI shifts the standard of obviousness considerably:
systematic search of huge solution spacesFast generation and optimisation of variants
Blurring of the boundary between inventive achievement and algorithmic routine
Transparency of the invention process:
The principle of disclosure requires that the technical teaching can be described in an understandable way. Many AI systems, especially black box models, make this difficult:
limited explainability of complex models
Difficulties in reproducing the results
Tensions between confidentiality and disclosure requirements
Differentiation from the state of the art:
As AI is based on existing data and solutions, new results are often close to what is known:
increased overlap with existing patents
increased risk of unintentional infringements
Uncertainty in determining the scope of protection
Systematic risks:
AI enables the mass generation of slightly varied solutions, which can be used strategically:
Increase in patent thickets
Overloading of patent offices
possible inhibition of innovation instead of promotion
Overall, it is clear that AI not only challenges patent law in certain areas, but also calls its fundamental assumptions into question. The decisive question is not so much whether adjustments are necessary, but whether patent law can treat AI as a mere tool in the long term - or whether it must adapt its protection logic to an increasingly machine-based innovation reality.
Where can SMEs in Baden-Württemberg find support for patent issues relating to AI?
SMEs in Baden-Württemberg can make use of targeted advisory services for questions relating to AI and patents, which are supported and funded by the Baden-Württemberg Ministry of Economic Affairs, Labour and Tourism. These services aim to support SMEs at an early stage, reduce legal uncertainties and strengthen the strategic handling of property rights in the innovation process.
Patentcoach BW The Patentcoach BW programme plays a central role here. It is aimed specifically at SMEs and offers individual, practical advice on questions of patentability, the development of an IP strategy and the categorisation of AI as a tool in the invention process. Particularly in the case of AI-supported innovations, the coaching helps to clearly define one's own role as an inventor and to prepare patent applications in such a way that they fulfil the legal requirements. The programme is not intended as a substitute for patent attorneys, but rather as an upstream orientation and competence building.
Patent and Trademark Centre BW In addition, the Baden-Württemberg Patent and Trade Mark Centre at the Stuttgart Regional Council acts as a low-threshold contact point for initial professional orientation. The centre provides SMEs with basic information on patents, trade marks and designs as well as information on the application process and current legal developments. The centre offers an important introduction to the topic, particularly for companies that are confronted with property rights or AI-based innovations for the first time.
Overall, the Baden-Württemberg Ministry of Economic Affairs thus provides an advisory network that links AI, innovation and patent law and supports SMEs in strategically safeguarding their technical developments at an early stage. In all of this, it is to be expected that patent law itself is also facing exciting innovations in dealing with AI in the innovation process.
