ARTIFICIAL INTELLIGENCE IN BUSINESS OPERATIONS: EXPLORING PRODUCTIVITY AND ACCEPTANCE

Ioana Ciofu (), Giulia Kondort (), Stefana Pop () and Roxana Cioc ()
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Ioana Ciofu: Bucharest University of Economic Studies, Romania Doctoral School of Business Administration I
Giulia Kondort: : Bucharest University of Economic Studies, Romania Doctoral School of Business Administration I
Stefana Pop: Bucharest University of Economic Studies, Romania Doctoral School of Business Administration I
Roxana Cioc: Bucharest University of Economic Studies, Romania Doctoral School of Business Administration I

Annals of Faculty of Economics, 2024, vol. 33, issue 2, 263-274

Abstract: This paper will provide information on the impact of AI in daily life and work-related activities.Today, AI functionalities could nowadays transform businesses, playing a critical role in enhancing and improving decisions. From virtual assistants to automation tools, AI covers a great amount of information, which could impact the core. In this paper, the productivity and sense of failure of AI will be paper. The productivity of AI, such as, varies by tasks and industry. AI could excel in repetitive and high-precision tasks. On the other hand, humans outperform AI in tasks requiring creativity and emotional intelligence. This qualitative study will show the perception of integrating AI into workflows and asking questions about value added. To evaluate the impact of artificial intelligence (AI) on business operations, an online survey was conducted to examine perceptions of AI's efficiency, adaptability, and fault tolerance.The analysis revealed generational differences in acceptance and trust towards AI. Younger respondents, particularly those under 25, were found to have greater tolerance for AI errors and a greater willingness to integrate AI into workflows. This is likely to reflect their familiarity with technology. In contrast, older respondents exhibited lower levels of trust and acceptance, particularly in contexts requiring precision, such as financial transactions. The results suggest that while AI is perceived as highly effective in repetitive and data-intensive tasks, its limitations in adaptability and emotional intelligence remain a concern. The findings emohasize the need for reskilling initiatives to facilitate workforce transitions and the development of ethical guidelines to address trust and reliability issues.

Keywords: Artificial Intelligence; Productivity; Failure; Problem-Solving; Consistency; Precision (search for similar items in EconPapers)
JEL-codes: M10 M15 (search for similar items in EconPapers)
Date: 2024
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