At the latest since the voice bot ChatGPT became known, the topic of artificial intelligence has finally moved into the public eye. It has a reputation for not only being able to change many industrial processes, but also for turning entire professions upside down or even making them disappear completely. According to many experts, however, the AI sector is only at the very beginning of its development, and the universally admired results of ChatGPT are just a foretaste of what AI could achieve in the near future.

An important aspect of the use of AI is the optimization of processes in companies, whereby concepts that fall under the umbrella terms AI and machine learning (ML) go hand in hand. Together with Intel and Kyndryl, software virtualization leader VMware demonstrated at the Hannover Messe how smart robotics based on AI and machine learning can take over quality assurance on the assembly line. This requires a lot of computing power, which in many cases has to be provided by high-performance data centers.

However, there are also application scenarios where computing power is required at the far edge. One example that Intel, Kyndryl and VMware also refer to is wind turbines, where the on-site use of AI is intended to optimize maintenance. In the case of highly automated AI decisions, it is obviously crucial how reliably the result of an AI can be evaluated, as the Fraunhofer Institute for Intelligent Analysis and Information Systems ISIA, based in Sankt Augustin near Bonn, emphasizes. Specifically, for example, an autonomous vehicle must be able to reliably recognize the objects and people in its environment so that it can react appropriately. A system for assessing uncertainty, which the institute is working on and which it presented at the trade fair, helps to assess whether the system's decision is trustworthy or whether certain fallback mechanisms need to be activated.

Thomas Meier, Chief Technologist at Hewlett Packard Enterprise, said: "AI is a core component of many of our products, such as servers, storage systems and networks. Among other things, AI helps our customers to optimize the performance of these systems and to predict and prevent problems." For years, millions of sensor data have been collected every second from systems around the globe and used to train AI, which in turn is intended to support users in operation and predictive maintenance. "Since 2010, we have analyzed more than a thousand trillion data points in this way and saved our customers more than 1.5 million hours of lost productivity," Meier continues.

Generative AI to accelerate digital change

A third of industrial decision-makers in medium-sized and large companies in Germany already believe that generative AI can accelerate digital change in their companies. This is the result of a representative survey of 1,500 industrial managers in Germany conducted by the opinion research institute Civey on behalf of Microsoft, as announced by the Windows company on the occasion of the Hannover Messe.

More than half (62%) of respondents even see multiple benefits for generative AI in industry. According to them, cost savings (51%), increased efficiency (45%) and the optimization of business processes (41%) are the main benefits. In addition, 42% of all respondents see the reduction of routine activities as a way of mitigating the shortage of skilled workers.

Nevertheless, only around eight % have used generative AI in their company to date. The practical use or plans for implementation obviously depend on the size of the company. More than a quarter of managers from large companies (1,000 employees or more) are already using or planning to use generative AI (28%). In smaller companies (up to 49 employees), the proportion is only half of this, namely 14%. For medium-sized companies (up to 999 employees), the figure is 18%.