The digitalization of industrial hardware, including factories, buildings, energy networks, and transportation systems, is generating enormous amounts of data. Technologies for data analysis and processing are needed to exploit the enormous economic potential of these data volumes.

AI is particularly important here. It is emerging as a key technology in the digital transformation. Using AI can optimize production processes, raising them to a new level of efficiency. AI therefore also significantly contributes to resource efficiency and sustainability.

Bringing AI to the Masses

Not only are companies in the electrical industry users of AI technologies in their own production, they are also providers of AI solutions for all sectors of the economy. However, many companies are still in the early stages of adopting AI. To bring AI applications and business models closer to these companies, the ZVEI has developed a white paper with specific use cases and will initiate corresponding research projects.

Industrial AI: Note the Differences

Solving industrial challenges is a distinct category of challenges in AI that often differs greatly from common use cases in the consumer sector. "Low-data" AI, which is based on smart data and combines AI with cybersecurity and edge computing — as opposed to cloud computing, which involves centralized data processing — is particularly important.

 

The areas of application are diverse, and technical, regulatory, and legal requirements can differ greatly between industrial sectors, as can risks. Therefore, overarching regulation or certification is not expedient.

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