The impact of artificial intelligence on business decision-making

Abstract

The integration of Artificial Intelligence (AI) in business decision-making patterns initiated a significant transition in artificial intelligence’s profession and value within the business world. This technology is able to expand primary business functions into new stages of advancement, shifting managerial competence capacity from limited to proactive. However, artificial intelligence adaptation also introduced couple of complex securities, governance, and ethical challenges. Artificial intelligence potential growth and expansion in the business world had shown evident, therefore it necessities the conduction of structured research and analysis of the impact it possess on enterprises, especially in managerial level. This thesis aimed to understand artificial intelligence influence on business decision-making patterns, including outcomes and challenges. This thesis explored and com-pared business decision-making competence prior and after artificial intelligence adoption. It also investigated artificial intelligence models and adoption trends, which inducted recent artificial intelligence adoption impact on companies’ decision-making and leaders actions towards these integrations in their core business processes. Another objective of this thesis was to analyse artificial intelligence adoption impact on business decision-making within key industries to understand artificial intelligence modifications in decision-making functions within these fields. Using secondary data based qualitative approach, this research investigated the nature and practical side of this impact deeply using multi-case study of global dominant companies. Through utilizing thematic analyses of scholarly articles with study cases, the research findings indicated three interconnected themes. Findings revealed a revolutionary shift in artificial intelligence adaptation pathway from just an automation tool into advanced strategic competence, backing management in deciding most convenient approach for their business. It achieved transitioning decision-making characterises to become predictive, proactive, high quality, speedy, and more reliable. However, research identified critical challenges correlated with artificial intelligence utilization change, including algorithmic bias and data security management which increases the necessity of cybersecurity protection and data governance system. Responding to these issues allows artificial intelligence-powered organizations in maximizing efficiency and avoid being ethically questioned. Overall, research concluded that artificial intelligence’s impact is the re-engineer of the business decision-making itself, but leaders should consider constant investments in artificial intelligence models, human-artificial intelligence talent development, and data governance.