AI as a catalyst for organizational learning: moving beyond tool implementation to learning transformation

Purpose This viewpoint examines how artificial intelligence (AI) is transforming organizational learning beyond mere tool implementation. It explores the shift from traditional learning paradigms to AI-enabled learning ecosystems, analyzing how organizations can effectively integrate AI while maintaining essential human elements in their learning processes. Design/methodology/approach The analysis synthesizes recent research and theoretical perspectives on AI in organizational contexts, focusing on implementation challenges and future implications. It draws upon current literature in organizational learning, AI implementation, and leadership development to construct a comprehensive framework for understanding AI-enabled learning transformation. Findings The successful integration of AI in organizational learning requires fundamental changes in organizational structure, culture, and leadership approaches. Organizations must balance technical implementation with human-centric learning strategies, developing new frameworks for measuring success and managing human-AI collaboration in learning processes. Research limitations/implications This paper primarily relies on theoretical frameworks and recent research findings, which may limit the generalizability of the conclusions. Future empirical studies are needed to validate the proposed concepts and explore the practical implementation of AI in diverse organizational contexts. Additionally, the rapid evolution of AI technologies necessitates continuous updates to the research to capture emerging trends and innovations. Practical implications Organizations need to develop comprehensive strategies for AI integration that address both technical and cultural challenges. This includes investing in new capabilities, redesigning learning processes, and developing leadership competencies for managing AI-enabled learning environments while maintaining human engagement. Originality/value This viewpoint provides a novel perspective on AI’s role in organizational learning by moving beyond implementation considerations to explore how AI can catalyze fundamental transformations in how organizations learn and develop. It offers insights for practitioners and researchers on managing the evolution toward hybrid learning organizations.

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Publication Details

Journal
Development in Learning Organizations An International Journal
Published
2025-04-14
DOI
https://doi.org/10.1108/dlo-11-2024-0326
Citations
5
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
6.21
Controls
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article

AI as a catalyst for organizational learning: moving beyond tool implementation to learning transformation

Eduardo Carlos Dittmar
5 citations
Development in Learning Organizations An International Journal
Digital Transformation in Industry
6.21
article

AI as a catalyst for organizational learning: moving beyond tool implementation to learning transformation

Eduardo Carlos Dittmar
article en
5 citations

Abstract

Purpose This viewpoint examines how artificial intelligence (AI) is transforming organizational learning beyond mere tool implementation. It explores the shift from traditional learning paradigms to AI-enabled learning ecosystems, analyzing how organizations can effectively integrate AI while maintaining essential human elements in their learning processes. Design/methodology/approach The analysis synthesizes recent research and theoretical perspectives on AI in organizational contexts, focusing on implementation challenges and future implications. It draws upon current literature in organizational learning, AI implementation, and leadership development to construct a comprehensive framework for understanding AI-enabled learning transformation. Findings The successful integration of AI in organizational learning requires fundamental changes in organizational structure, culture, and leadership approaches. Organizations must balance technical implementation with human-centric learning strategies, developing new frameworks for measuring success and managing human-AI collaboration in learning processes. Research limitations/implications This paper primarily relies on theoretical frameworks and recent research findings, which may limit the generalizability of the conclusions. Future empirical studies are needed to validate the proposed concepts and explore the practical implementation of AI in diverse organizational contexts. Additionally, the rapid evolution of AI technologies necessitates continuous updates to the research to capture emerging trends and innovations. Practical implications Organizations need to develop comprehensive strategies for AI integration that address both technical and cultural challenges. This includes investing in new capabilities, redesigning learning processes, and developing leadership competencies for managing AI-enabled learning environments while maintaining human engagement. Originality/value This viewpoint provides a novel perspective on AI’s role in organizational learning by moving beyond implementation considerations to explore how AI can catalyze fundamental transformations in how organizations learn and develop. It offers insights for practitioners and researchers on managing the evolution toward hybrid learning organizations.

Development in Learning Organizations An International JournalVol. 40(1)
Universidad Rey Juan Carlos (ES)
Openalex Percentile: Top 4%
Digital Transformation in Industry
6.21
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