AI in Industry

Coordinators: Robert Sablatnig, Martin Kampel

AI-powered systems can automate various tasks, reducing the need for manual intervention and speeding up processes. This leads to improved efficiency and productivity in industries such as manufacturing, healthcare, transportation, and retail. AI enables the automation of repetitive and mundane tasks, freeing up human resources to focus on more complex and creative activities. This leads to increased efficiency, productivity, and cost savings in manufacturing, logistics, and customer support industries. AI systems can analyze vast amounts of data, identify patterns, and make informed decisions quickly and accurately. This capability is particularly valuable in finance, healthcare, and marketing, where complex data analysis is crucial for making informed choices. AI can use machine learning algorithms to forecast future outcomes based on historical data patterns. This capability is valuable in various applications, including demand forecasting, risk assessment, fraud detection, and preventive maintenance, enabling proactive decision-making. AI systems can perform tasks with high precision and accuracy, surpassing human capabilities in areas such as image recognition, natural language processing, and data analysis. This improves outcomes, reduces errors, and increases reliability in various fields. AI algorithms can accurately detect and recognize objects within images or videos. This capability is valuable in areas like surveillance, autonomous vehicles, quality control, and augmented reality, where identifying and tracking objects is essential. They can classify images into predefined categories or provide relevant tags. This helps in organizing and searching large image databases, content moderation, recommendation systems, and personalized marketing. With advancements in hardware and AI algorithms, real-time data processing is now feasible. AI has the potential to revolutionize healthcare by analyzing medical data, assisting in diagnoses, and predicting patient outcomes. It can help identify patterns in medical images, recommend treatment plans, and aid in drug discovery, ultimately improving patient care and saving lives. These few examples highlight the transformative power of AI, enabling numerous applications across industries and enhancing efficiency, accuracy, and safety. However, applications of AI depend also on explainable AI (xAI) methods (trustworthiness, fairness, explainable procedures) and different levels of transparency to be accepted by society and to allow ethical AI. This SIG fosters collaboration among experts in various fields of AI and its applications to propel the field forward and identify potential avenues for future research.


  • Robert Sablatnig, TU Wien, Faculty of Informatics


  • Co-Chair: Martin Kampel, TU Wien, Faculty of Informatics

Board Members

  • Eva Eggeling, KI4LIFE: Fraunhofer Austria Innovation Center for
  • Digitalization and Artificial Intelligence
  • Michael Hödlmoser, emotion3D GmbH Vienna
  • Mlađan Jovanović, Univerzitet Singidunum, Belgrade
  • Hannes Kaufmann, TU Wien, Faculty of Informatics
  • Bernhard Krüpl-Sypien, Crowdranking GmbH Vienna
  • Georg Langs, Medical University Vienna
  • Andreas Maier, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
  • Martina Marchetti-Deschmann, TU Wien, Faculty of Technical Chemistry
  • Gerhard Schuetz, TU Wien, Faculty of Physics
  • Markus Vincze, TU Wien, Faculty of Electrical Engineering and Information Technology
  • Matthias Zeppelzauer, St. Poelten University of Applied Sciences