Returning to the initial question and the subjective feeling: There is an exciting phenomenon, namely that we humans only look linearly at the development of such technologies. That is, we see a state of growth and think it will perhaps be 10 or 20 percent better the following year. But if we compare this with other technologies of the recent past, such as cloud storage, CPUs, and so on, the reality is that these technologies are improving exponentially.
Therefore, we would have to assume that today's AI progress will not be 10 to 20 percent better in a relatively short time; therefore, we would but four times, ten times, or twenty times as good. And then an exponential curve emerges, which, of course, becomes steep at some point. Exactly when it begins, the effects of surprise are created. Then, you go from one quantum leap to the next and are surprised by the enormous progress.
Let's look at the impact of AI on our working world. That artificial intelligence will change our work, how we work, and the work itself is less surprising. What we are seeing now, however, in light of current developments, is that generative AI is penetrating areas that we humans initially considered our untouchable core competence, for example, creativity and knowledge work. How do you assess the situation: Will AI disrupt disrupt that we didn't have in mind before?
I read a book the other day that painted a future scenario in which care workers and craftsmen drove Porsches, and the knowledge workers were the ones who had relatively low-paid jobs.
It's a bit of an upside-down world from today's perspective. But that is actually what could be the consequence of this technology now.
I remember three or four years ago; I was on the road with a presentation to media companies where I showed the potential that exists when you automate media value creation via software. At that time, there were already excellent examples from other industries, such as Shopify. Shopify. At that time, I wanted to show that the building blocks for this were there. GPT already existed at that time, and it was also foreseeable that at some point, with images and videos, it would come to this. As far as being ready. While giving this lecture, I noticed something exciting: The creative people, the journalists and so on remained firmly convinced that technological progress would not disrupt their business.
However, knowledge work and creativity are, excitingly, the first things that are perhaps really at risk of disruption. disruption-at risk.
There are no reliable studies yet, but there are initial forecasts on the market, statements that go in the direction that knowledge workers would be able to work 36 percent more efficiently through generative AI, for example. Which, thought the other way round, would mean that perhaps 36 percent fewer knowledge workers would be needed. There is also much speculation about what the current developments could mean for software development. One scenario could be that the marginal costs for software development, for example, could also approach 0, as has already happened historically with other things. For example, with memory prices, bandwidth, or CPUs. This would have the effect of making software development cheaper and cheaper. This would mean that salaries in software development would decrease, we could work more effectively, and software development would become more affordable.
This is great for me as an "innovation person", of course, because the biggest obstacle to prototypes and MVPs has been that software development is simply so expensive. Assuming it would come to that and software development would only cost a fraction of what it costs today, you can develop and build much more customized software and are no longer so dependent on commodity software. Commodity commodity software. That would have a significant impact on the tech industry.
Software development is just one example. The same is true for a knowledge worker like me. In my job, it's about absorbing a lot of information from different sources, storing it, and developing solution-oriented concepts. This is precisely what the Large Language Models can do quite well: draw insights from various data pots, derive conclusions, and generate outputs, for example, in a PowerPoint. As a knowledge worker, I am a candidate who would prefer to do at least part of my tasks augmented by AI in the future. I deliberately say increased, because I don't believe people will completely replace knowledge work. Instead, I think that we can work in a more leveraged way, concentrate more on our core tasks, and use AIs to eliminate tedious tasks and take complexity out of the work.
Finally, wherever there is knowledge work, the question must be asked: Do we still need the same number of knowledge workers as before, or do we need architects who have the big picture and the vision in their heads?
I think these questions have to be asked now in every industry and every business. And ask them quickly because we live in a "cloudified"world. For example, Microsoft Office and comparable software come from the cloud today. The productivity levers are there as soon as AIs are integrated into these products, from one day to the next.
As a company, you should then, of course, quickly know what the implications are for your processes, your business model, etc.
You are also working with Bertelsmann Group colleagues on this topic to clarify issues. What would you share from these experiences? How should companies position themselves now?
The most important thing in advance: you always think you are too late. The ChatGPT topic and Generative AI have been top-of-mind in the market. Nevertheless, from my point of view, it is not too late. It is precisely the right time to think through the issue calmly and systematically without rushing.