The future of work and education in AI-driven innovative systems: A systematic literature review and lexicometric analysis

IF 6 2区管理学 Q1 BUSINESS

International Journal of Management Education Pub Date : 2025-06-20 DOI:10.1016/j.ijme.2025.101221

Gulab Kumar, Dipanker Sharma, Bhawana Bhardwaj

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引用次数: 0

Abstract

Purpose

The present study aims to analyze the impact of AI-driven innovative systems on work and education by exploring available literature settings covering variables such as artificial intelligence, innovation, work, and education (AIWE), as well as examining the collective domain of AIWE through applied theories, contextual settings, and methodology. Additionally, it considers potential directions for future AIWE research.

Design/methodology/approach

This study conducts a lexicometric analysis of 146 literature along with a systematic literature review of 64 studies published from 1997 to 2024 to comprehensively explore the collective domain of AIWE. It examines prevalent topics of study, publication status, citation patterns, as well as elements of the theory-context-method and antecedents-decisions-outcomes framework used in the field of AIWE research.

Findings

The current review highlights crucial insights for educational authorities, managers, and policymakers to address challenges posed by technological advancements. Numerous theoretical frameworks, contextual elements, applied methodologies as well as factors such as antecedents, decisions, and consequences have been identified. The review contributes to the field of AIWE domain by offering a comprehensive analysis of more than two decades and provides valuable insights to guide future research toward future preparedness within regional innovation systems.

Originality/value

Our article emphasizes the need for further study by presenting a structured review of the collective domain AIWE research. It helps stakeholders of territorial innovation systems to develop strategies to prepare academic institutions and the workforce for an AI-driven future, guide future research, and provide practical information on the factors and fundamentals of the domain of AIWE.

查看原文本刊更多论文

人工智能驱动的创新系统中工作和教育的未来：系统的文献综述和词汇计量学分析

本研究旨在通过探索涵盖人工智能、创新、工作和教育（AIWE）等变量的现有文献设置，以及通过应用理论、上下文设置和方法检查AIWE的集体领域，分析人工智能驱动的创新系统对工作和教育的影响。此外，它还考虑了未来AIWE研究的潜在方向。本研究对146篇文献进行了词汇计量学分析，并对1997年至2024年发表的64篇文献进行了系统的文献综述，以全面探索AIWE的集体领域。它考察了流行的研究主题，出版状况，引用模式，以及在AIWE研究领域使用的理论-上下文-方法和前因-决策-结果框架的要素。研究结果当前的综述强调了教育当局、管理者和政策制定者应对技术进步带来的挑战的关键见解。已经确定了许多理论框架，上下文元素，应用方法以及诸如先决条件，决策和后果等因素。该综述通过对20多年的综合分析为AIWE领域做出了贡献，并为指导未来研究区域创新系统的未来准备提供了有价值的见解。原创性/价值我们的文章通过对集体领域的AIWE研究进行结构化的回顾，强调了进一步研究的必要性。它帮助区域创新系统的利益相关者制定战略，使学术机构和劳动力为人工智能驱动的未来做好准备，指导未来的研究，并提供有关人工智能领域因素和基础的实用信息。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Management Education Multiple-

CiteScore

10.30

自引率

25.00%

发文量

136

审稿时长

64 days

期刊介绍： The International Journal of Management Education provides a forum for scholarly reporting and discussion of developments in all aspects of teaching and learning in business and management. The Journal seeks reflective papers which bring together pedagogy and theories of management learning; descriptions of innovative teaching which include critical reflection on implementation and outcomes will also be considered.