Using artificial intelligence for decision-making in management
Artificial intelligence (AI) is referred to as the core element of the “fourth industrial revolution.” According to recent estimates by the McKinsey Global Institute, AI has the potential to boost global economic activity by around US$13 trillion by 2030.
AI is being used to an increasing extent for decision-making in management, both in a variety of industries (e.g. healthcare, banking, education, manufacture, retail) and in functions (e.g. marketing, operations). In marketing, for example, AI can predict loss of business 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 inferior quality and ultimately improve the quality of products.
The recent advances in AI research hold promise for decision-making in businesses and organizations. Driven by increases in data access and computing power, and by the ongoing development of algorithms, modern AI algorithms are capable of emulating human decision-making and discernment. This enables AI to augment and automate a large number of management decisions in business organizations. Overcoming existing obstacles in the introduction of AI into corporate governance calls for an interdisciplinary perspective at top management level.
The central topic of this Ladenburg Roundtable is the development, implementation, and evaluation of new AI technologies that support decision-making in management. A distinguishing feature thus takes the form of innovative algorithms from the field of AI (e.g., explainable AI, generative AI, large-scale language models, probabilistic ML, or causal ML), which pave the way for new insights in practice and beyond. This holds great potential for information and the improvement of decision-making. In particular, a network is being planned as an interdisciplinary initiative in the field of AI technology and business research in an integrated format.
The networking via the Ladenburg Roundtable aims to strengthen German AI research, which is at the interface to decision-making in management. In particular, the main goal is to expedite research into the development, implementation, and evaluation of new AI methods to support decision-making within companies and organizations. This can also lead to new innovations for business models.