Call for paper: Workplace Learning in the Era of Generative AI

Workplace Learning in the Era of Generative AI

The rise of sophisticated generative AI systems has transformed organizational approaches to learning and development (Maity, 2019). As workplaces adapt to this technological shift, they face critical challenges, including accelerating skill obsolescence (World Economic Forum, 2023), growing demand for personalized learning, and the need for scalable, cost-effective training solutions beyond emerging work models (Santana & Cobo, 2020).

However, the integration of generative AI into workplace learning raises critical questions about professional expertise, human judgment, and the evolution of professional development (Carvalho et al., 2022). AI-driven learning environments challenge traditional models of skill development, shifting the balance between structured learning programs and on-demand, adaptive learning experiences.

To achieve these aims, we invite contributions that critically assess the opportunities, challenges, and ethical considerations of AI-mediated learning in various organizational contexts. By fostering interdisciplinary discourse, this collection will provide a nuanced perspective on best practices, emerging trends, and future directions for AI-driven learning in the workplace. Through this approach, the special issue will contribute to both academic scholarship and practical insights, helping organizations develop more effective, inclusive, and sustainable AI-integrated learning strategies.

List of topic areas

Case studies of generative AI integration in workplace learning: in-depth analyses of how organizations have successfully or unsuccessfully implemented generative AI in corporate training and professional development programs, success factors and barriers to AI adoption in workplace learning.
AI-driven innovations in training delivery and assessment: the role of generative AI in adaptive learning, personalized learning pathways, and intelligent tutoring systems. AI-generated training content and its impact on learner engagement and knowledge retention.
Frameworks and models for integrating generative AI into organizational learning processes: strategies for managing resistance to AI-driven training approaches; leadership and managerial perspectives on AI-driven learning adoption.
Evolution of professional roles and competencies: how AI is reshaping job roles, particularly in knowledge-intensive professions; the role of AI in identifying skills gaps and providing personalized learning recommendations; the emergence of new AI-driven roles such as AI trainers, AI ethicists, and digital learning architects.
Changes in workplace learning culture and practices: the shift from traditional training models to AI-powered continuous learning; the influence of AI on informal learning, peer learning, and social learning networks; employee attitudes and perceptions towards AI-assisted learning, skills adaptation and reskilling initiatives.
Perspectives on how AI is revolutionizing talent management through workforce development, integration of personalized learning, team-based skill enhancement, and strategic organizational planning.

Submissions Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available here.

Author guidelines must be strictly followed. Please see here.

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to ““Please select the issue you are submitting to”.

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.