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Journals / Acta Infologica / 2026 / Volume: 10 Issue: 1

Large Language Models in the Business World: Usage Areas, Benefits, Impacts, and Future Perspectives

Mehmet Fatih Karaca(TOKAT GAZIOSMANPASA UNIVERSITY)0000-0002-7612-1437
Kürşat Aslan(TOKAT GAZIOSMANPASA UNIVERSITY)0009-0007-4397-5798
Pages
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Publication Date
2026-06-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This study contributes to the literature by offering an integrated qualitative framework that simultaneously links business value creation, workforce transformation, and implementation challenges, positioning LLMs adoption as a holistic phenomenon encompassing socio-technical and organizational phenomenon rather than a purely technological advancement.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Large Language Models (LLMs) have become a central component of digital transformation in business organizations.
📊
Key Findings & Data:Rather than considering LLMs holistically, existing research often tends to focus on their applications, organizational benefits, employment effects, or implementation challenges as separate dimensions.
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Conclusion & Impact:This study contributes to the literature by offering an integrated qualitative framework that simultaneously links business value creation, workforce transformation, and implementation challenges, positioning LLMs adoption as a holistic phenomenon encompassing socio-technical and organizational phenomenon rather than a purely technological advancement.
🔬Design:Review & Systematic Survey
📍Scope:2018 Verileri
⚙️Variables:Large Language Model · Natural Language Processing · Artificial Intelligence

Abstract

Large Language Models (LLMs) have become a central component of digital transformation in business organizations. Rather than considering LLMs holistically, existing research often tends to focus on their applications, organizational benefits, employment effects, or implementation challenges as separate dimensions. To address this gap, this study provides an integrated qualitative examination of the use of LLMs in the business world, focusing on their application areas, organizational benefits, impacts on employment and job transformation, limitations, and future potential. The study adopts a qualitative document analysis design. A systematic review of publications from 2018 to 2025 was conducted using internationally recognized academic databases and reputable industry sources. Qualitative content analysis was undertaken on the collected documents using a deductive-inductive thematic framework aligned with the study’s research questions. LLMs are extensively applied across multiple business functions, including human resources, customer service, data analysis and reporting, content creation and marketing, financial analysis, market intelligence, legal document processing, corporate training, and automation-integrated systems. LLMs adoption enhances organizational efficiency, supports cost optimization, and improves managerial decision-making by enabling rapid, data-driven, and scenario-based insights. In terms of employment, LLMs primarily drive task-level automation and job role transformation rather than direct job displacement, increasing the importance of higher-order skills such as critical thinking, supervision, and digital literacy. Despite these benefits, the study identifies persistent challenges related to ethical risks, data security and privacy, model bias, hallucinations, and governance mechanisms. This study contributes to the literature by offering an integrated qualitative framework that simultaneously links business value creation, workforce transformation, and implementation challenges, positioning LLMs adoption as a holistic phenomenon encompassing socio-technical and organizational phenomenon rather than a purely technological advancement.

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Cite This Article

Karaca, M. F., Aslan, K. (2026). Large Language Models in the Business World: Usage Areas, Benefits, Impacts, and Future Perspectives. Acta Infologica, Volume: 10 Issue: 1. https://doi.org/10.26650/acin.1663665

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