INFLUENCE OF ARTIFICIAL INTELLIGENCE ON BUSINESS DECISION-MAKING

Oleksandr Kubatko; Stanley Ozims; Viacheslav Voronenko

doi:10.32782/mer.2024.103.03

Oleksandr Kubatko Sumy State University https://orcid.org/0000-0001-6396-5772
Stanley Ozims Sumy State University
Viacheslav Voronenko Sumy State University https://orcid.org/0000-0002-0301-5924

DOI: https://doi.org/10.32782/mer.2024.103.03

Keywords: decision-making, business, demographic characteristics, decision accuracy, contribution, artificial intelligence (AI)

Abstract

The paper delves into the influence of artificial intelligence (AI) on business decision-making. By examining this phenomenon's technical, strategic, and ethical dimensions, the study seeks to unravel the implications that artificial intelligence integration brings to decision-making. The study conducted a comprehensive analysis to investigate the perceptions and experiences of individuals regarding integrating artificial intelligence in business decision-making. The study involved a detailed examination of demographic characteristics, artificial intelligence awareness, implementation status, perceived impact on decision-making speed and accuracy and ethical considerations related to bias in artificial intelligence-driven decision-making. The findings show that the gender and age distribution of respondents influence the perception and use of artificial intelligence in business decision-making. And artificial intelligence-driven decisions are dominant in the healthcare sector. Furthermore, artificial intelligence awareness and implementation indicated a generally positive outlook, with significant acknowledgement and familiarity among respondents. There is a positive perception of artificial intelligence making decisions faster with a positive contribution to the accuracy of business decisions. However, there is a record of some biases in artificial intelligence-driven decision-making. This highlights a significant concern in the fair and equitable application of artificial intelligence algorithms. This shows the importance of addressing biases to ensure ethical decision-making. The hypothesis testing sought to ascertain whether the incorporation of artificial intelligence is contingent on the accuracy of business decisions. The chi-square test results indicated insufficient evidence to propose a noteworthy relationship between the integration of artificial intelligence and decision accuracy. This implies that organizations should explore additional factors influencing decision accuracy, recognizing that artificial intelligence integration alone may not be the sole determinant.

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