Artificial Intelligence and Operational Research Towards Finance Management: A Research Agenda

Efstratios Livanis, Nikolaos F. Matsatsinis and Fotis C. Kitsios ()
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Efstratios Livanis: University of Macedonia
Nikolaos F. Matsatsinis: Technical University of Crete
Fotis C. Kitsios: University of Macedonia

A chapter in Operational Research in the Era of Digital Transformation and Business Analytics, 2023, pp 179-186 from Springer

Abstract: Abstract Businesses today, as a result of the globalization of entrepreneurship and rapid advancements in information and communication technology, must employ the most appropriate tools and methods to remain competitive in the marketplace. Artificial intelligence has the potential to play a significant role in this. Over the last few decades, artificial intelligence, and particularly machine learning, has become increasingly well-established in the fields of academic research and commercial application. According to recent research, the development and acceptance of artificial intelligence technology could result in a 14% increase in global GDP by 2030 due to the development and use of artificial intelligence technology. Businesses, on the other hand, must completely rethink their business models to be successful, integrate artificial intelligence technology into their business processes and adopt an artificial intelligence strategy. A lot of research is being done about how machine learning and operational research work together, which is a new field. The main purpose of this paper is to highlight and analyze the impact of artificial intelligence in business and finance and its added value to operational research. Thus, we give an overview of how artificial intelligence and machine learning can be used in business and finance from an operational research point of view.

Keywords: Artificial intelligence; Machine learning; Operational research; Finance; Business (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-24294-6_19

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DOI: 10.1007/978-3-031-24294-6_19

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