Suche auf der Schloss Dagstuhl Webseite
Sie suchen nach Informationen auf den Webseiten der einzelnen Seminare? - Dann:
Nicht fündig geworden? - Einige unserer Dienste laufen auf separaten Webseiten mit jeweils eigener Suche. Bitte beachten Sie folgende Liste:
Schloss Dagstuhl - LZI - Logo
Schloss Dagstuhl Services
Innerhalb dieser Seite:
Externe Seiten:
  • DOOR (zum Registrieren eines Dagstuhl Aufenthaltes)
  • DOSA (zum Beantragen künftiger Dagstuhl Seminare oder Dagstuhl Perspektiven Workshops)
Innerhalb dieser Seite:
Externe Seiten:
Innerhalb dieser Seite:
Externe Seiten:
  • die Informatik-Bibliographiedatenbank dblp

Dagstuhl-Seminar 24342

Leveraging AI for Management Decision-Making

( 18. Aug – 21. Aug, 2024 )

Bitte benutzen Sie folgende Kurz-Url zum Verlinken dieser Seite:




Artificial intelligence (AI) is increasingly being used for management decision-making, both across a variety of industries (e.g. healthcare, banking, education, manufacturing, retail) and functions (e.g. marketing, operations). In marketing, for example, AI can predict business failures and thus act as an early warning system when service quality needs to be improved. In business process management, AI can help identify causes of poor quality and ultimately improve product quality.

Recent advances in AI research are promising for decision-making in companies and organizations. Driven by increases in data access, computing power, and algorithm advancements, modern AI algorithms are able to mimic human decision-making and judgment. This enables AI to complement and automate a variety of management decisions in business organizations. Overcoming existing hurdles in introducing AI into company practice requires an executive and interdisciplinary perspective.

The central topic of our Dagstuhl Seminar is the development, implementation, and evaluation of new AI technologies to support decision-making in management. A distinguishing feature is therefore innovative algorithms from the field of AI (e.g. explainable AI, generative AI, large language models, probabilistic ML, causal ML, etc.) that enable new insights in practice and beyond. This holds great potential for informing and improving decision-making.

Copyright Stefan Feuerriegel, Foster Provost, and Galit Shmuel

  • Artificial Intelligence
  • Machine Learning

  • Management
  • Business
  • Decision-making
  • Applications
  • Marketing