AI and robotics dominate Hannover Messe

The omens for this year’s Hannover Messe seemed to mirror the general global political situation. Between tension and economic uncertainty, many industries are operating in an environment shaped by crisis rhetoric, investment pressure and strategic realignment. The fact that, of all times, local public transport in Hanover went on strike on the Monday and Tuesday at the very start of the fair fitted almost seamlessly into this picture.

The expansive exhibition grounds felt unusually airy and in some places almost a little thinned out. Not in the halls themselves – there the familiar trade fair scene prevailed, with well‑filled stands, conversations and heavy footfall. But across the outdoor areas as a whole, the impression was hard to avoid that previous editions had once been broader in scope and that more halls had actually been occupied.

The importance of automotive topics also seemed to have been greater in the past. Hannover Messe is becoming more and more of a cross‑industry technology showcase, in which the automotive sector is no longer so naturally one of the defining forces as it was in earlier years. Even so, it will still be worth looking to Hanover in 2026.

This was most evident once again in the topic of artificial intelligence. AI was once again the all‑pervading theme of this trade fair in 2026. It was noticeably harder to find stands where it did not play a prominent role than those where it was deliberately pushed into the spotlight. This was not only about software or data models in the narrow sense, but about the broader narrative of more productive planning, smarter automation and more resilient value chains. AI was staged as the link between engineering, production and control, and thus as a key technology for an industry under intense pressure to adapt.

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At the same time, the halls showed how broad the trade fair’s technology spectrum has now become. On the centre stage in Hall 26, senior decision‑makers spoke throughout the week about the pressing questions of the day. Alongside players from automation and industry, representatives of the defence sector also came visibly to the fore. In Hall 25, in turn, this thematic shift became almost physically tangible. Future topics such as humanoid robotics and battery use cases stood side by side with a strikingly expansive presence of defence and armaments themes. It was precisely this juxtaposition that made clear how strongly the industrial debate is currently shifting, and how closely questions of technological innovation are now intertwined with geopolitical realities.

Siemens sees itself as an indispensable partner

The presence of Siemens blended seamlessly into this picture of an industry under enormous pressure to accelerate while at the same time searching for new technological direction. In hall 27 the company presented itself with a force that was hard to miss at the trade fair. Talking to Kristian Kozole, vice president automotive DACH at Siemens Digital Industries Software, it quickly became clear how Siemens understands its role in this transformation. It is no longer just about offering individual tools or software modules, but about making entire development and production processes faster, more end to end and more controllable. “Speed is the new currency,” says Kozole.

Especially for the automotive industry, which is caught between software pressure, shorter product cycles and growing integration complexity, this is more than just a trade fair slogan. Siemens is positioning itself as a partner for companies that want to further virtualise their development, shorten simulation loops and accelerate the transition from engineering to manufacturing. At the fair, this ranged from the digital maturity model for long established brownfield structures to PAVE 360, a software defined vehicle digital twin that makes it possible to map control units and vehicle environments in the cloud at an early stage in order to ease integration problems before the start of series production.

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At the same time, Kozole linked Siemens’ presence directly with one of the guiding themes of this trade fair, namely the next generation of robotics. Siemens sees particular potential for the automotive industry in the coming years in the interplay between AI, simulation and the digital thread. “We believe that the topic of humanoid robots, for example, will also be an essential component in the future of manufacturing,” said Kozole. Siemens does not build its own humanoid robots, but sees itself as an enabler for their development, industrialisation and subsequent operation. The decisive factor here is to secure as much as possible digitally at an early stage, to simulate movement sequences and to master in advance the integration challenges between mechanics, electronics and software.

Humanoid robots as an opportunity for suppliers

The fact that this topic moved so visibly to the forefront in Hannover also fits with a recent analysis by McKinsey. According to this, humanoid robotics is developing at high speed from a spectacular demonstrator into a potential billion-euro market. This shift is being driven by advances in AI and hardware as well as by sharply rising investment. At the same time, the market ramp-up is determined less by the vision than by industrial feasibility.

At the centre is the question of how quickly complex hardware can be produced economically in large quantities. This opens up a new value creation field especially for suppliers. The opportunities are particularly strong in precision components, special gearboxes, sensors and, above all, actuators, which according to McKinsey account for up to 60 percent of the total costs of humanoid robots.

From the perspective of the automotive industry in particular, this is noteworthy because familiar industrial strengths intersect here with a new market. Batteries, semiconductors and power electronics can build on existing structures from the automotive and electronics industries. Europe, and Germany in particular, also have strong capabilities in precision components, safety electronics, system integration and certification. At the same time, the path to the mass market remains difficult. High costs, low volumes and supply chains that are not yet sufficiently scaled are slowing development.

Alliances move into focus

Fittingly, new alliances also came into view in Hanover, showing how strongly the robotics field is currently moving towards scalable ecosystems. Neura Robotics, for example, announced a strategic collaboration with AWS to bring physical AI more quickly to industrial scale. AWS will become the central cloud infrastructure for the Neuraverse platform, which will handle training data, real-time processing and the exchange of intelligence across entire robot fleets. At the same time, Neura plans to link its so-called Neura Gym training environments with AWS services such as Amazon SageMaker to accelerate the connection between real sensor data and high-resolution simulation. This is complemented by a sales partnership via the AWS Partner Network and the prospect that Amazon will test Neura robotics in selected fulfilment centres.

AWS itself also used the trade fair to position itself as an infrastructure partner for scaling industrial AI. The central thesis was that the real bottleneck for many industrial companies is no longer testing individual AI applications, but rather rolling them out across complex value chains. AWS therefore highlighted an approach that tightly interlocks cloud infrastructure, data platforms and different AI models. The aim is to overcome fragmented data landscapes and turn isolated applications into end-to-end industrial systems. One of the reference customers was the Volkswagen Group, which uses its Digital Production Platform to link 43 plants in a central factory cloud and deliver more than 1,200 AI applications.

The Chinese technology company Lenovo also focused in Hannover primarily on the question of how to move AI from the pilot phase into real factory operations and, in collaboration with Nvidia, showcased several use cases with direct relevance for the automotive industry. At its core, this was about connected quality control using computer vision, edge AI and digital twins to identify errors in ongoing production processes earlier, analyse root causes faster and correct deviations before they trigger downstream problems.

“Manufacturers do not need any more AI pilot projects. They need AI that works at scale in production,” says Jonathan Wu, chief technology officer for intelligent manufacturing at Lenovo. Added to this were autonomous intralogistics solutions with multifunctional robots for line supply, picking, kitting and material transport between production stages – precisely the processes that determine stability and takt capability in car plants as well. This was complemented by AI-supported supply chain management with real-time transparency across multiple tiers, along with edge infrastructures for visual inspection, predictive maintenance and autonomous systems.