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Artificial intelligence is finally moving to the center of political attention.
The current coalition agreement makes it clear: Germany wants to strategically promote AI – as a central component of innovation and economic policy. The goal is ambitious: Germany is to become the leading AI nation in Europe.
This shows how urgent the issue is and that the need for action has been recognized.
That’s a good thing. Because the potential is there: with a strong Mittelstand sector, committed founders and growing technological expertise, Germany has all the prerequisites to play a pioneering role in the field of AI.
Reclaim German pioneers spirit! Hello German inventor mentality! Glad you’re back! Business, the tech scene and politics are finally pulling together. And let Germany not only catch up, but also help shape the path of AI. Right at the forefront. Very innovative. And, of course, in the European way – in other words, very responsibly.
In the eyes of the uninformed, the German Mittelstand may have a cliché attached to it: solid, hard-working, a little traditional, a little dusty. Kind of old school. But anyone who believes this cliché is yesterday’s news! Because what goes on in the Mittelstand sector may even give America and China a run for their money.
Veit Brucker from Asana, a specialist in digital transformation and the implementation of AI-supported work processes, immediately throws a remarkable figure into the audience: according to an internal study, 94% of German managers state that the processes in their company are in need of innovation.
So the need is huge, the hunger is great, the problem is on the agenda. Other recent studies show that around 33% of small and medium-sized enterprises (Mittelstand) in Germany will already be actively using artificial intelligence (AI) by 2025. And 24% of the Mittelstand are currently testing AI solutions, meaning that more than half of Mittelstand are either already using AI or are currently working on introducing it.
Of course there is still room for improvement. But we can see from conferences like Hinterland of Things that old-school has been slamming with new-school for a few years now and that both are doing the best business together. Start-ups and Mittelstand have set out to leave the beaten track and increase productivity. In production and manufacturing, logistics and supply chain, retail and customer service:
• Production and manufacturing: e.g. through predictive maintenance or quality control via image analysis
• Logistics and supply chain: through dynamic route planning, warehouse optimization or risk analysis
• Retail and customer service: with automated systems for demand forecasts or support
Wherever the process pressure is high, and the recurring tasks are many.
So the question is not even which sector can benefit the most. Rather, which one cannot.
Is it just like that? Can a traditional industrial company just merge with a hip AI start-up and suddenly everything is solved? How do you explain to the older generation that their “always done this way” was successful, but that there is a better way? And who actually learns from whom? One thing is clear: people, their mutual openness and collaboration is the key.
Lena Weirauch from aiomatic puts it in a nutshell: “You have to ask yourself on both sides whether you have the same expectations.” Thomas Paulus, Chief Digital Officer at KSB, also emphasizes: “You really have to talk a lot to bring the different cultures together”.
As this is so often the case, the solution to mediocrity lies exactly in the middle: When established processes are combined with modern technologies, new paths suddenly emerge. Shortcuts that lead to the top.
It’s clear that AI is the topic that you really can’t avoid anywhere and that even the average Joe has heard something about (at least since it was included in the coalition agreement).
Pip Klöckner, investor and tech analyst, spoke about the Gartner Hype Cycle, a graphical model that depicts the various phases of the life cycle of new technologies. According to this model, we have just reached the point where the first doubts about AI are emerging. “Large language models are slowly becoming interchangeable. Which provider will be the winner in the end?” Perhaps the solution – also for Germany – lies in open source solutions.
Frank Thelen is even clearer: “What has always annoyed me is that we never had a global market leader in Germany in the first wave of digitalization. And it’s really important to me that Europe remains independent”. So now it’s time to actively shape the next steps of the hype cycle up to the plateau of productivity and turn AI into an economic force in Germany.
Speaking of hype: the Pope in a trendy puffer jacket. Many people found it funny because it looked so real that everyone fell for it. The image was created with AI. Gaza as a glitzy luxury travel destination was less funny. Because here, too, many people believe they are dealing with the truth. This video was also AI-generated.
Both show how important morals and ethics are when it comes to representing or faking the truth. Or rather, the dilemma begins with the training of an AI: if care is not taken from the outset to ensure that no shenanigans are committed here, you will soon have a huge social problem, hashtag right-wing violence, hashtag fascism, hashtag (space for your own creepy suggestions). Pip Klöckner warns of so-called “cognitive offloading”: “We will lose the ability to think critically if we outsource everything to AI.”
So morals and ethics are more important than ever. Because when it comes to work in the manufacturing industry, the use of AI is also increasingly raising the question: will we soon no longer be needed at all? Leonie Althaus from traide AI comments: “For now, the responsibility remains with people. But then the job will change in the direction of controlling. There will no longer be so many clerical, operational areas. New professions will emerge.”
Yes, AI can analyze weld seams, optimize stock levels and maintain machines with foresight. And that’s all well and good and helps us move forward. But it can’t sense whether a team is overwhelmed. It has no intuition, no responsibility, no context. In industry in particular, we need both: systems that read data and people who recognize the meaning in it.
If you want to survive in a competitive environment, there is no way around AI. And if you want to create a future worth living, you also need people. Period.
Companies such as remberg or Cerrion rely on AI to relieve the burden on skilled workers, not replace them. So instead of people using their eyes, ears and hands to search for faults in systems, an AI does this and detects potential faults at an early stage.
Because, to quote Leonie Althaus again: “Some things nobody wants to do because they’re boring as fuck.”
In turn, people can use the time gained to do things that they can do much better than machines: Making decisions, thinking of solutions, tackling problems, drinking coffee and communicating.
Conversely, AI can also help when less gut feeling is required, but data-based decisions are needed instead. Evaluating relevant data more quickly and incorporating it into decisions shortens decision-making processes enormously. And makes many a salesperson sigh with happiness.
To conclude from all of this that AI will be used more rather than less is not an ambitious thesis. It is a consequence of the shortage of skilled workers, the pressure to innovate and the desire to remain competitive in all of this.
© 2024 Hinterland of Things
