A Reality check of the benefits of LLM in business
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Abstract (arXiv)
Large language models (LLMs) have achieved remarkable performance in language understanding and generation tasks by leveraging vast amounts of online texts. Unlike conventional models, LLMs can adapt to new domains through prompt engineering without the need for retraining, making them suitable for various business functions, such as strategic planning, project implementation, and data-driven decision-making. However, their limitations in terms of bias, contextual understanding, and sensitivity to prompts raise concerns about their readiness for real-world applications. This paper thoroughly examines the usefulness and readiness of LLMs for business processes. The limitations and capacities of LLMs are evaluated through experiments conducted on four accessible LLMs using real-world data. The findings have significant implications for organizations seeking to leverage generative AI and provide valuable insights into future research directions. To the best of our knowledge, this represents the first quantified study of LLMs applied to core business operations and challenges.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 32 of its 54 references that are in the map. First posted on arXiv 9 Jun 2024.
Builds on
32 of 54 references.
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20 more
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Built on by
Citing papers per year: 2025: 5.
5 papers.
- 2025PersonaBOT: Bringing Customer Personas to Life with LLMs and RAGcited by 2
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- 2025Hallucination Detection with Small Language Modelscited by 0
- 2025The Algebra of Meaning: Why Machines Need Montague More Than Moore's Lawcited by 0
- 2025Agentic NL2SQL to Reduce Computational Costs16 Oct 2025
- 2025The Algebra of Meaning: Why Machines Need Montague More Than Moore's Law8 Oct 2025
- 2025Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks25 Jul 2025
- 2025Hallucination Detection with Small Language Models24 Jun 2025
- 2025PersonaBOT: Bringing Customer Personas to Life with LLMs and RAG22 May 2025