Mapping the Impact of AI Agents on Business Performance: A Bibliometric Approach

Badiu Irina (), Anagnoste Sorin () and Savastano Marco ()
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Badiu Irina: Bucharest University of Economic Studies, Bucharest, Romania
Anagnoste Sorin: Bucharest University of Economic Studies, Bucharest, Romania
Savastano Marco: Sapienza University of Rome, Italy

Proceedings of the International Conference on Business Excellence, 2025, vol. 19, issue 1, 3492-3510

Abstract: The way companies currently interact with their customers is due to the evolution of Artificial Intelligence (AI), especially through Artificial Intelligence Agents. Many organizations have realized that they can defeat their competitors in numerous sectors by using computer technology, mainly AI, to enhance their functions, which minimize cognitive loads for the employees and allow very personalized customer interactions. Despite these advantages, challenges related to ethics, data security, transparency, and user trust remain pressing concerns. To dissect how they develop and are converted into results, the companies initially should know which approaches they should adopt and what the consequences are on business size. While we are diving into the impact of Artificial Intelligence Agents on corporations, an important point should be figured out – the expansion of a strong comprehension of the research field. Likewise, an essential point is represented by the establishment of an overview of the theoretical framework offered by the specialized literature. To map the research landscape and identify trends and gaps in the scientific literature, a bibliometric analysis was conducted on 106 scientific articles published between 2019 and 2024. This study uses co-occurrence analysis and co-citation in VOSviewer to map the intellectual structure of the field and to discover the most considerable research clusters and the research areas needing further exploration. The dimensions inquired are AI-owned customer personalization, automation-gained cost efficiencies, and AI-induced corporate decision making through augmented roles.

Keywords: AI Agents; Customer Support; Operational Optimization; AI-driven personalization; Automation; Bibliometric Analysis (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:poicbe:v:19:y:2025:i:1:p:3492-3510:n:1029

DOI: 10.2478/picbe-2025-0267

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