After addressing the question of what artificial intelligence (AI) can actually be in the first article in this series, here we pose the - somewhat provocative - follow-up question: Why do we need AI at all? And why does it make sense to take a closer look at it right now?
These questions do not arise from technological actionism, but from the observation of a change that has long since begun. The discussion surrounding artificial intelligence is as multifaceted as it is dynamic: it ranges between promises of efficiency and fears of losing control, between potential and practice. But one thing is undisputed: AI is not a passing phenomenon, but an expression - and catalyst - of a structural technological upheaval. The crucial question is no longer whether we should engage with AI, but how we want to do so - with what attitude, what objectives and which partners.
And yet current data from the digital association Bitkom shows a differentiated mood within the industry:
- 50% of companies initially observe the experiences of others.
- 42% do not (yet) see themselves as sufficiently equipped to integrate AI into existing processes.
- And 21% even consider AI to be a hype that will soon be over.
- At the same time, over 79% are calling for German industry to play a pioneering role in AI.
We know from our day-to-day conversations with company representatives: The will to shape is there. The challenge lies not in accessing technologies - but in understanding their profound significance and being able to generate concrete options for action from them. There is often still a large gap between the recognition of AI as a future technology and its actual application.
Unrealistic today, standard tomorrow
AI is not just a new technology. It is a profound paradigm shift that fundamentally influences the way we make decisions and work. We cannot assume that the development of AI will follow linear patterns. On the contrary, it is contingent - in other words, it is fundamentally open, unpredictable and dependent on contexts, decisions and cultural interpretations. AI development does not follow a roadmap, but is more like a network of possible paths. This is precisely why design is so important - because it does not work towards a fixed goal, but rather helps to shape the goal.
But it also means that what seems unrealistic today may be standard tomorrow. And what is considered leading technology today may be outdated tomorrow. Those who wait for AI until it is "ready" not only miss out on creative power but, in the worst case, also lose the autonomy of entrepreneurial self-determination.
So what to do? Anyone who uses AI for process automation or efficiency gains has set a very important course. However, if we fundamentally reduce AI to these areas, we run the risk of missing its structural significance and therefore also its deeper potential.
New series of articles from the AI Alliance
The rapid development of artificial intelligence (AI) is challenging us all - especially in small and medium-sized enterprises (SMEs) and municipal institutions.
In this series of articles, we would like to shed light on and discuss essential questions relating to artificial intelligence - from the meaning of individual technical terms, ethical and moral issues or the interaction between humans and machines, to the classification of global developments at regional level and the management of regulatory challenges - always with a clear focus on the fields of application in business and society.
About the author: Dr. Jan Zipp is responsible for AI Strategy & Innovation and Community Management at the KI-Allianz in Tübingen. He has been working in the AI and deep tech sector in Germany and abroad for over ten years. His focus and publications are in the field of institutional and artificial (computational) creativity research, human-machine interaction and the impact of AI on the future of human work.
A new form of division of labor
One approach that has long been present in scientific discourse and is now slowly gaining importance in business practice is that of augmentation. Artificial intelligence is not seen as a replacement for human labor, but as a technological system that specifically contributes to productively supporting human strengths - for example in areas such as creativity, intuition or complex decision-making. In this augmentative understanding, AI does not compete with humans, but complements and reinforces them.
We know from creativity research: AI systems are particularly valuable when they are not creative instead of humans, but structure creative processes, help overcome mental blocks and suggest new associations - not because they are original like a human, but because they help recognize other patterns, change perspectives, in short: expand the space of what is possible and conceivable. In this sense, AI solutions can serve as catalysts. This is especially true where human abilities such as intuition or empathy are particularly pronounced and our own attention is particularly selective or biased.
This complementary role is not a weakness of AI - on the contrary, it is an expression of a new form of division of labor between humans and machines. And it opens up previously untapped areas of innovation - provided that AI is not seen as a substitute, but rather as an amplifier of human potential, which must be promoted accordingly.
Exploiting potential - not despite, but because of uncertainty
To put it bluntly: AI is not just another tool. It changes the conditions under which tools are used at all. A functional approach to AI (keywords: automation and optimization) is often a sensible or even necessary first step. But what to do with the resources freed up? How to use and even recognize potential? What can follow is a deeper reflection on what we want to do - and why.
SMEs actually have the best prerequisites for this: Small and medium-sized enterprises in particular have access to high-quality data that is often not publicly available. This data is of great value for the use and training of AI-supported systems - especially if it is combined with industry-specific expertise and there is a willingness to experiment with it with an open mind and think beyond existing business models.
"AI is an imposition - in the best sense of the word!"
The strategic relevance of this approach is evident not least in the geopolitical context. Digital sovereignty, i.e. the ability to shape technological developments independently and in a self-determined manner, is becoming a question of location. Our discussions with companies show: A lot is happening. Even contradictions that were long considered irreconcilable - such as the pressure to innovate and the scarcity of resources - can increasingly be resolved productively. The momentum is high. And it can be shaped.
We are under no illusions: It all takes time, competence building and institutional learning processes. But innovation does not mean perfection. Above all, it means developing an understanding of what we want to achieve through and with AI - even if this goal only becomes clearer or changes during the process.
AI is an imposition - in the best sense of the word! It forces us to change our perspective. And at the same time, it opens up new possibilities beyond our previous routines and thought models. Those who take on this challenge will be rewarded with new insights and new creative power. AI provokes new ways of thinking. This is precisely where its real productive power lies.
The dynamics are there. Innovation cycles are faster, and expectations in terms of orientation and legal certainty are higher for good reason. A pioneering role in AI development, as almost 80% of industrial companies would like to see, requires the courage to take on a lot ourselves by thinking beyond automation and optimization and recognizing and using the augmentative potential of AI - together with partners from research, municipalities and entrepreneurship. Then perhaps soon it will no longer be 50% of manufacturing companies that wait and see what others do. But hopefully significantly fewer.
