Artificial intelligence has already become a defining technology across a wide range of industries; Bosch argues that mobility is now firmly part of that shift. While people still sit behind the wheel, the basic operation of modern vehicles, as well as the safety of passengers and road users, is increasingly shaped by sensors, software and AI-based algorithms.
That was the context in which Bosch presented its latest developments at the international event in Budapest on May 21-22. The company used the symposium to underscore how AI is being integrated into both vehicle functions and the production systems that support them.
István Szászi, the representative of the Bosch group in Hungary and the Adriatic, said the company is working to turn AI-based technologies into practical and safe solutions for transport and industry. Bosch has already filed more than 2,000 AI patents globally and plans to invest more than EUR 2.5 bln worldwide in artificial intelligence by 2027.
One of the main themes of the symposium was the role AI can play in advanced driver assistance systems. Bosch said these systems can help vehicles see, sense, and correctly interpret information from their surroundings, recognize traffic situations, make decisions and react on the road in real time.
Bosch says machine vision, situational awareness and spatial orientation are no longer being treated simply as research topics. The company is presenting them as technologies moving closer to practical use in future mobility solutions.
That is an important distinction. The automotive sector has spent years discussing intelligent driving systems in theoretical terms. Bosch’s emphasis in Budapest was different: it tried to position AI as a functional technology that can be embedded in real products, rather than as a long-range concept.
The company argues that AI in the automotive sector creates real value only if it can move beyond theory and become a dependable product function for series production. That includes not only how a car perceives the road around it, but also how it interprets risk, supports the driver and reacts under real operating conditions.
Bosch also linked these developments directly to the wider progress of automated driving. The company’s position is that better AI-based sensing and interpretation are not separate from that path, but part of its foundation.
A major focus of the Budapest event was the growing importance of what happens inside the vehicle. Bosch Research’s Oliver Lange, who is responsible for the company’s interior sensing field, said safety can no longer be understood only in terms of the car’s external environment.
New safety regulations, NCAP ratings and rising consumer expectations are all accelerating the development of in-cabin sensing, creating what Lange described as an increasingly intelligent protective shield inside the vehicle. In Bosch’s view, these AI-based innovations not only strengthen safety in a narrow sense but also support further progress in automated driving.
That part of the presentation was closely tied to road safety data. Bosch cited international studies showing that one in 10 traffic accidents is linked to driver fatigue, drowsiness or distraction. Under the EU’s General Safety Regulation, fatigue-monitoring systems have already been mandatory in new vehicles since 2024. From July 2026, systems designed to ensure that drivers’ attention is not diverted while driving will also become compulsory.
Bosch said its AI-based interior safety developments are intended to address these requirements while expanding what in-cabin safety systems can do.
The company is developing a range of interior sensing solutions that combine cabin cameras and interior radar to monitor both the driver and the entire passenger compartment. AI-based safety functions can then use the data collected by these systems to warn, fine-tune settings or intervene where necessary.
One of the priority areas Bosch highlighted is vital-sign monitoring, especially the estimation of heart rhythm and breathing rate. The aim is to detect medical irregularities before the driver becomes incapable of acting. In a critical situation, the system could warn the driver or even bring the vehicle to a safe stop.
Bosch also described how AI-supported interior monitoring can detect a broader range of risks. A 3D body posture detection system can recognize when an occupant is sitting in a way that could increase injury risk in an unexpected event, such as placing feet on the dashboard or sitting too close to an airbag.
By estimating occupants’ height and weight, the system can optimize airbag deployment. It can also monitor whether the driver keeps their hands on the steering wheel and detect children accidentally left inside the vehicle.
Taken together, these developments show how Bosch is widening the definition of automotive safety. The company’s point is not only that the vehicle must better understand the road around it, but also that it must better understand the people inside it.
The symposium also made clear that Bosch sees AI as part of industrial production, not just part of the final product. The company said AI and machine-learning-based methods are being used in the development of complex automotive MEMS sensors (Micro-Electro-Mechanical Systems, tiny devices that combine mechanical components and electronic circuits on a single silicon chip), in automated quality control for soldering processes and in identifying the hidden causes of unwanted rattling, vibration and friction in vehicle components such as airbag electronics.
Bosch argues that these methods can help identify problems before series production begins, improving both development speed and final product quality. In other words, AI is being positioned not only as something that changes what a vehicle can do, but also as something that changes how it is engineered and manufactured.
Another example Bosch highlighted was its joint GraphRAG technology with Sztaki, Hungary’s Institute for Computer Science and Control. Bosch described it as an AI-based enterprise knowledge center that can be used across research and development, engineering and quality management.
By finding precise answers in large volumes of unstructured material, such as PDFs and reports, the system is designed to speed up problem-solving for engineers and researchers and make it easier for new specialists to join ongoing projects. It is a less visible use of AI than autonomous driving or cabin monitoring, but one that may be just as important for industrial efficiency.
This article was first published in the Budapest Business Journal print issue of June 19, 2026.
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