What is AI (Artificial Intelligence)?

AI, or Artificial Intelligence, is technology that enables systems to independently learn, reason and make decisions based on data β€” without every scenario having to be programmed in advance.

AI makes machines and software β€˜smart’: they adapt, recognise patterns and improve themselves.

In industrial contexts, AI is increasingly applied to automation, quality control, maintenance and process optimisation.


🎯 Examples of AI applications

Application Examples
Predictive Maintenance AI predicts component failures based on vibration or temperature data
Visual quality control AI algorithms detect defects via camera images of the production process
Process optimisation AI automatically determines optimal setpoints based on real-time data
Energy management AI optimises consumption based on production planning and grid load
Anomaly detection AI detects abnormal behaviour in OT systems or networks

🧯 Why is AI relevant?

  • Increases accuracy and speed in decision-making
  • Learns from both historical and real-time data
  • Reduces human error
  • Helps uncover complex patterns invisible to humans
  • Supports the automation of tasks and processes

πŸ” AI vs. traditional algorithms

Traditional automation AI-based systems
Pre-programmed rules Learn from data and adapt based on context
Reacts predictably Can respond dynamically and contextually
Difficult to scale or reuse Self-learning and scalable across multiple applications
Often reactive Can act proactively and predictively

🏭 Specifically in OT/industrial environments

  • AI models run on Edge Computing or IPCs close to the machine
  • Integration with SCADA, MES or Historian data for insights
  • Continuous training of models based on operational performance
  • AI can act as digital operator support for troubleshooting or setpoint advice

πŸ“Œ In summary

AI makes systems smarter, faster and self-learning β€” and is therefore a key driver behind Smart Industry and IT/OT convergence.