This ‘Gramsci gap’ can also be observed in industry: between the end of old business models and the stable emergence of new technologies, a productive but risky vacuum arises. Disorientation. Hesitation. Disruption.
AI alone is not the revolution
The hype surrounding AI easily obscures the big picture. AI is not the sole driver of the next wave, but only part of it. The real revolution lies in the combination of technologies.
- Bio-based chemistry is replacing fossil molecules with renewable ones.
- Biopharma is fundamentally changing drug development.
- Sustainability goals require new evaluation standards in processes.
- AI, in turn, creates new control options for highly complex systems.
All these megatrends are based on one raw material: data. And this data must be extracted from the processes. This is where our responsibility as engineers begins.
Technology provides data and creates value
The foundation for data-driven business models, smart services and adaptive production systems is created where sensor technology, control, process control technology and IT converge. Those who establish a continuous data chain from the field device to the cloud are laying the foundation for change.
Technologies such as Ethernet APL already provide the physical basis for high-speed data communication, even from explosion-proof zones. What was once considered a niche topic is becoming standard.
But infrastructure alone is not enough. Change requires the application of new data models such as DEXPI, open platforms that enable interoperability, and the consistent use of digital twins that span the entire plant lifecycle – from planning and operation to decommissioning.
Discrepancy between necessity and attitude
However, a recent VDI study from May 2025 shows that less than 40 percent of engineers surveyed in Germany expect AI to fundamentally change their working environment in the near future. This stands in stark contrast to a Gartner forecast that by 2027 at the latest, 80% of the technical workforce will be forced to expand their Artificial Intelligence skills.
This cognitive dissonance between requirements and expectations poses a risk for the region. While the US is directing massive investments into digital and green technologies with the Inflation Reduction Act and China is connecting platforms and production, hesitation prevails in Europe. The fact that AI courses will be compulsory for primary school pupils in China from autumn 2025 and that the number of engineering students in China is around three times higher than in Europe gives an idea of what the future competitiveness of European and German engineering might look like.
Conclusion: Act now – or be swept away by the wave!
The sixth Kondratieff wave is rolling. And it is not a trend that can be ignored. Europe has a lot going for it: excellent education, an outstanding ecosystem of industry, skilled workers and researchers, one of the world's largest economies and ethical standards. What counts now is the courage to implement change, openness to new ways of thinking and the willingness to understand digitalisation as a core industrial competence.
