A systematic literature review of large language model applications in industry

Moenks, Norbert; Penava, Pascal; Büttner, Ricardo

doi:10.1109/ACCESS.2025.3608650

A systematic literature review of large language model applications in industry

Publication date

2025-09-10

Document type

Übersichtsartikel, Überblicksdarstellung

Author

Moenks, Norbert

Penava, Pascal

Büttner, Ricardo

Organisational unit

Hybrid Intelligence

DOI

10.1109/ACCESS.2025.3608650

URI

https://openhsu.ub.hsu-hh.de/handle/10.24405/24014

Publisher

IEEE

Series or journal

IEEE access

ISSN

2169-3536

Periodical volume

13

First page

160010

Last page

160033

Peer-reviewed

✅

Part of the university bibliography

✅

Funding(s)

Publikationsfonds der HSU/UniBw H

Language

English

Keyword

Large language model

LLM use cases

LLM application

Industry

Systematic literature review

Porter value chain

Abstract

Large Language Models are rapidly transforming processes across industries by enabling advanced capabilities in natural language understanding, code generation, diagnostics, and decision support. Despite the growing adoption of this technology, a systematic understanding of their application across the industrial value creation processes remains lacking. This paper addresses this gap by conducting a systematic literature review of 96 peer-reviewed studies, following the PRISMA guidelines. Based on this foundation, large language model use cases across industries were identified, categorized, and structured using the primary and secondary activities of Porter’s value chain as a classification framework. The analysis reveals that LLM adoption is heavily concentrated in technology-focused and internal operational activities across industries, where they offer immediate benefits at lower risk. In contrast, areas such as logistics, procurement, and customer-facing functions remain largely unexplored, mainly due to challenges related to integration, data governance, and regulatory requirements. The analysis shows that current deployments are primarily limited to isolated, manageable use cases, leaving substantial innovation potential unrealized in underexplored value chain activities. These findings provide a foundation for further research and for the strategic adoption of large language models throughout the industrial value chain.

Description

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

Version

Published version

Access right on openHSU

Metadata only access