Mechanical engineering 2026: Between crisis and comeback

Economic conditions and framework

The restart of the German mechanical engineering sector in 2026 takes place against the backdrop of a persistent economic downturn and generally restrained investment willingness. The German Engineering Federation (VDMA) estimated in the fall of 2025 that the real production of the industry would decline by about five percent in 2025 and only increase by about one percent in 2026 - a signal for stabilization, but still far from a robust upswing. The industry therefore does not speak of growth dynamics, but of a "stagnation at a low level," where companies primarily need to optimize cost structures and sharpen their portfolios.

Overall economic expectations also remain subdued. The Ifo Institute forecasts only very slight real growth of 0.2% for Germany in 2025 and a somewhat stronger recovery of 1.3% in 2026, which, after several weak years, is more to be seen as a bottoming out rather than a boom phase. At the same time, the Institute for Employment Research (IAB) warns that while fiscal stimuli and support programs provide support, employment growth remains limited by demographic developments and structural bottlenecks in the labor market.

Added to this are geopolitical burdens that particularly affect the export-oriented mechanical engineering sector. Trade conflicts, US tariffs on steel and aluminum, ongoing uncertainties in important sales markets, as well as high and volatile energy prices increase planning risks and squeeze margins. In this environment, the VDMA demands a clear response from the EU to US subsidy programs, a swift implementation of industrial policy measures, and a strengthening of the European internal market to stabilize supply chains and secure the international competitiveness of companies.

Skilled workers, labor market, and demographic change

The labor market remains a central bottleneck factor for mechanical engineering - across all qualification levels. The IAB forecasts that the number of employed persons in Germany will slightly decrease again in 2026: After an increase of about 10,000 employees in 2025, a decline of around 20,000 people is expected in 2026. Particularly critical is that at the same time, a decline in employment of 130,000 people in 2025 and 70,000 people in 2026 is expected for the manufacturing industry, forcing companies to increase productivity and automate work more.

The engineering monitor from VDI and IW shows that despite the cooling economy, the level of open positions for engineering and IT professions remains exceptionally high. In the second quarter of 2025, the number of open positions fell by 22.1%, but with 106,310 open positions, it remained at a high level. For companies, this means: even in phases of weaker demand, recruitment, retention, and qualification of skilled workers remain strategic core tasks.

The Federal Institute for Vocational Education and Training (BIBB) points out that a shortage of skilled workers always exists when the demand for qualified workers permanently exceeds the supply - that is, over several years and not just in an economic peak. The "adjusted search duration" is an indicator available to measure these bottlenecks and shows how difficult it is to fill positions in individual professions. Additionally, BIBB and the QuBe project create medium-term forecasts to identify technical bottleneck professions early and to expand training capacities and further training offers in a targeted manner.

The demographic development structurally exacerbates the situation. The potential workforce will only grow slightly in 2025 and will begin to shrink from 2026 onwards, as large birth cohorts retire and are not fully replaced. The BIBB warns in this context, especially for technical professions, of increasing bottlenecks. For mechanical engineering, this means: companies must align their HR strategies in the long term - from more attractive working conditions to flexible working time models and internationalization of recruiting to systematic further training to prepare existing employees for new tasks in digitalization, automation, and sustainability.

Digitalization and new investment priorities

Despite economic headwinds, investments in research and development (R&D) remain a central strategic element on a global level. The study by Bain & Company shows that global spending on engineering and R&D services (ER&D) is expected to grow by around 10% annually until 2026, despite uncertain economic conditions. Digital engineering areas such as AI, cloud, and IoT are developing particularly dynamically, with annual growth of around 19% expected. The majority of the more than 500 executives surveyed plan to increase their ER&D budgets despite the economic downturn.

At the same time, the global competition for talent is increasing significantly. According to Bain, 73% of companies report a shortage of engineers and IT specialists, especially in digital expertise in areas such as data analysis, AI development, cybersecurity, and system architectures. Many companies are responding by outsourcing R&D tasks to specialized engineering service providers, building global collaboration networks, or establishing their own 'centers of excellence' for digital technologies.

Another driver is the shift towards outcome-oriented business models. Pay-per-use concepts, equipment-as-a-service, and lifetime performance contracts mean that machine builders are more involved in the operation and performance of their installed base. Digital twins, continuous data collection, and AI-supported analyses thus become not only technical tools but core components of new business logics, for example, to detect errors early, shorten time to market, and offer new services.

Digital twins, industrial metaverse, and new factory planning

The industrial metaverse is evolving from a vision to a toolbox for concrete industrial applications. The Fraunhofer Institute for Production Systems and Design Technology (IPK) describes the industrial metaverse as an immersive, connected digital ecosystem that links the real industry with the virtual world. Digital twins form the technical basis for this by virtually mapping products, systems, and processes, supplying them with real-time operational data, and enabling visualization, analysis, optimization, and safe simulation of complex processes.

In factory planning, virtual models allow different layouts, material flows, and energy setups to be tested before physical investment is made. Virtual commissioning reduces the risk of costly errors on the construction site and shortens ramp-up times because controls, processes, and safety scenarios are tested in advance. Additionally, immersive training scenarios allow employees to train complex maintenance or setup processes in VR/AR without blocking the real system or taking safety risks. Furthermore, digital twins and AR support facilitate remote maintenance by displaying live data and context-related information directly in the service technician's field of view.

In the long term, a network of interconnected digital twins, shared data spaces, and standardized interfaces will emerge in the industrial metaverse. Fraunhofer IPK emphasizes that connected, scalable systems link devices in global factory networks, and sovereign data spaces enable secure exchange between partners. In combination with AI, edge, and cloud computing, this creates a foundation for semi-autonomous and prospectively autonomous production systems as well as data-driven business models.

Sovereign computing infrastructure: The industrial AI cloud

The industrial AI cloud creates a new level of digital infrastructure specifically tailored to industrial requirements. Deutsche Telekom and NVIDIA are investing around one billion euros in an AI data center in the Munich region, which is scheduled to go into operation at the beginning of 2026. The platform is based on up to 10,000 NVIDIA GPUs and suddenly increases the available AI computing power in Germany by around 50%.

The cloud is intended to form the core of a “Germany stack”, in which SAP provides a unified basis for companies' own applications with the business technology platform. For mechanical engineering, this means access to highly scalable computing power for AI models, digital twins, and complex simulations - from virtual vehicle development to production optimization to robotics and computer vision applications. Siemens and other industry partners emphasize that on this basis, complex digital twins and simulation-based development can be rolled out much faster and more widely.

From the perspective of politics and industry associations, the industrial AI cloud also represents a political signal. The German government and participating companies view the project as evidence that Germany is an attractive location for digital future investments and that a sovereign AI infrastructure can be built in Europe. If this infrastructure can be widely anchored in mechanical engineering, it could become an important competitive advantage for data-driven business models "made in Europe."

Sustainability and hydrogen as growth drivers

Alongside digitalization, the transition to a climate-neutral industry is high on the agenda. The VDMA sees hydrogen and power-to-x technologies as key levers for decarbonizing the industrial sector and points to new value chains from renewable power generation through plant engineering to applications in mobility, chemistry, and process heat. Mechanical and plant engineering is considered a key industry here, as it provides the necessary components and systems for the generation, transport, storage, and use of hydrogen.

This creates additional demand impulses for mechanical engineering: manufacturers of electrolyzers, fuel cells, compressors, turbomachines, heat pumps, storage and recycling technologies are serving growing "green" markets. Studies in the context of the VDMA show that fuel cell and hydrogen technologies can be associated with significant additional value creation and employment potential for European mechanical engineering. Companies that consistently align their product portfolios with these "green" growth topics can position themselves as technology partners of the energy transition in the medium to long term.

For the industry, the question increasingly arises of how sustainability can be anchored as an integral part of business models. This includes lifecycle assessments, CO₂ balances, new service offerings for operational efficiency optimization, as well as take-back and remanufacturing concepts. It is precisely here that digital technologies and sustainability strategies interlock, for example, when digital twins are used to optimize energy and resource use over the entire lifespan.

Role of companies and business models

The mechanical engineering companies are responding to this mix of cost pressure, skilled labor shortage, digitalization, and sustainability requirements with a variety of measures. Many companies are launching innovation programs, building internal digital and AI teams, or working more closely with start-ups and technology partners. At the same time, collaborations with universities and research institutions are becoming more important to gain faster access to new technologies and qualified graduates.

A survey shows that 82% of German industrial companies consider artificial intelligence crucial for their future viability. At the same time, experts warn that AI applications are only scalable if they are based on a unified IT and data platform and do not remain stuck in numerous isolated solutions. Companies are therefore working to harmonize data, build governance structures, and introduce standardized interfaces.

Three major AI application areas are emerging:

• Trend detection for better transparency and forecasts through analysis of large data sets.
• Real-time decisions for rapid, AI-supported interventions directly on machines and systems using edge computing.
• Agentic and physical AI for autonomous systems such as robots, driverless transport systems, and software-supported co-pilots in production and service.

Consulting studies confirm the trend towards outcome-based models, where services are increasingly provided "as a service" and digital twins are used to accelerate development and improve customer outcomes.

Outlook: Opportunities despite headwinds

German mechanical engineering is heading into 2026 with headwinds, but also with clearly defined strategic fields of action. Economically, a sideways movement is more likely than a rapid upswing, and structural change in the labor market will keep the personnel situation permanently challenging. At the same time, value creation and competition are increasingly shifting towards digital, data-based, and sustainable business models.

Companies that now invest in R&D, digital skills, modern computing infrastructure, and new partnerships can emerge stronger from this transformation phase. The combination of digital engineering excellence, AI-supported services, industrial metaverse, green technologies, and reliable ecosystems offers the opportunity to grow profitably even in a challenging environment. If the mechanical engineering sector succeeds in decisively leveraging these factors, 2026 can become a year in which the course is set for competitiveness in the coming decade.