Artificial intelligence in the skilled trades

Artificial intelligence means that human actions are imitated by a machine (or robot) in such a way that it can process and solve problems independently. In future, for example, craft businesses will be able to have physically demanding work carried out by robots that “learn” these tasks and also take into account disruptive factors in the work environment. The use of artificial intelligence is also conceivable in the office, for example in accounting or occupational safety.

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Technology and use

Technology description

In recent years, almost all trade businesses have successfully mastered the first steps on the path to digitalization. Various information and data are digitally recorded, stored, forwarded and processed. With the topic of AI (artificial intelligence), another wave of digitalization is now rolling towards the skilled trades sector, acting as an innovation turbo for the development of new business models, processes, products or services. AI makes it possible to analyze the content of digital data and use it to create value. And thanks to machine learning, AI-based systems often even outperform experts. In addition, the Internet of Things (IoT), cloud technology and the associated communication and collaboration in real time will enable all trade businesses to access all relevant customer data and measured values in the future, meaning that AI can also be used in a variety of ways for remote diagnostics, maintenance and repairs. AI-based, mobile robots can also assist tradespeople in their daily work and relieve them of difficult and physically demanding tasks. Overall, AI offers enormous potential to make trade businesses more future-proof, more customer-friendly and, above all, more profitable.

Possible application scenarios

  • Machine learning
  • Data Mining
  • Occupational safety
  • Customer communication

Opportunities for SMEs

More efficient analysis of operating data

Automation of accounting

Optimization of customer communication

Quality improvement through optical image recognition

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