Editorial

I am pleased to present the special issue of Management and Labour Studies on the theme ‘Emerging Trends in Artificial Intelligence (AI) for Industry and Education: Opportunities and Challenges’. The Special Issue, published in collaboration with Xavier Institute of Management and Entrepreneurship (XIME, Chennai), is dedicated to its visionary leader and founder, Dr Joe Philip (21 May 1936–21 February 2026). The special issue contributes to the growing body of research on the impact of AI on management education and practice. The special issue received an overwhelming response, attracting hundreds of submissions owing to the timeliness and relevance of the theme. The editorial team at Management and Labour Studies has carefully read each manuscript submitted before making an initial decision of whether to send it out for external review. After thorough scrutiny of the manuscripts and multiple rounds of review, we accepted four manuscripts that offer interesting and novel insights into emerging trends in AI and its evolving role in management education and practice.

The onset of AI technology has offered solutions to business problems, enhanced learning and teaching experiences, and paved the way for new innovations. However, the challenges of integrating technology with contextual realities and identifying the unethical use of AI are areas of inquiry this Special Issue seeks to explore. The findings of the studies provide insights into the changing landscape of management education fostered by technological advancements and throw light on the unexplored constructs of technology acceptance.

A study by Delina and Kumar examines MBA students’ receptiveness to generative AI tools. It analyses factors such as gender differences, usage frequency and digital knowledge to assess what drives or hinders students’ use of AI. The study employs a statistical hypothesis-testing approach to evaluate the relationship between variables. The study underscores the importance of technology-driven management education and advocates a shift towards skill-based, future-oriented pedagogy.

Rao and Mathivanan investigate the factors influencing the academic integrity of postgraduate management students in an AI-integrated learning environment. The findings of the paper, based on data-driven statistical and thematic analyses, demonstrate that the students’ unethical use of AI is influenced by a combination of factors such as personal and social factors and institutional perception. The study contributes to integrity research in AI-mediated contexts, where academic integrity is not just a matter of individual morals but also shaped by external factors.

In another research, Varghese, Devassia and Abraham argue that effective integration of AI into teaching is possible through a pedagogy-centric approach. To evaluate the relationships among TPACK constructs and assess the moderating effect of teaching experience, responses from 150 faculty members at top B schools were collected. The study’s findings reveal that familiarity with AI technology is not enough; the faculty need to contextualize it to enhance the learning experience.

A quantitative cross-sectional study conducted by Rani and Metilda investigates how management students in India perceive and adopt generative AI tools to meet their educational needs. The study enquires whether overall satisfaction mediates the relationship between student perception and their future usage intentions. The key findings indicate a strong relationship among user experience, perceived versatility and educational impact, asserting perceived versatility as a strong independent predictor of satisfaction and usage. The students value AI tools that support diverse learning styles and meet their dynamic, interdisciplinary learning needs.

Overall, the articles in this Special Issue make a meaningful contribution in evaluating causal relationships, suggesting teaching models and gathering data on AI opportunities and challenges.

We thank the authors who submitted their research for possible publication, the reviewers for their invaluable assessment and feedback, and the editorial team for their rigorous scrutiny, constructive suggestions and timely decision-making. We hope the authors of the rejected manuscripts will not be discouraged from sending their research to Management and Labour Studies. I hope the thought-provoking articles featured in this special issue will stimulate a new wave of scholarship and advance meaningful discourse on the role of artificial intelligence in management education and practice.