Generative artificial intelligence and the reshaping of managerial capabilities

Introduction

This special issue sets out to advance how the field understands and practises management development. Generative artificial intelligence (AI) is changing managerial work at speed, and it raises pressing questions for management development (Raisch and Krakowski, 2021). Widely used tools such as ChatGPT, Microsoft Copilot and DeepSeek now draft reports, summarise meetings, analyse data and generate options in seconds, work that once filled a manager’s week. Management development has long assumed that the core of a manager’s work, and so the capabilities to be developed, would remain broadly stable. That assumption no longer holds. The manager’s task is shifting from producing work to directing it, checking it, and judging when it can be trusted, and managers are increasingly answerable for output they did not create and cannot always trace. Research has begun to examine how generative AI reshapes managerial work and how far it should share in managerial decisions, but the field of management development has yet to establish how managers should be prepared for it (Dixit and Jatav, 2024; Plotkina and Sri Ramalu, 2024). There is therefore a need for fresh evidence on what managers must now be able to do, and how those capabilities can be built.

Building on this need, the special issue invites papers that pose and address important questions about developing managers for generative-AI-reshaped work. Contributions may build or challenge theory, take earlier studies further, investigate practice as it emerges, or draw together existing evidence, and we place no restriction on method: quantitative, qualitative, experimental, field-based, mixed and meta-analytic work are all welcome, as are strong conceptual and review pieces. Because generative AI reshapes managerial work differently across functions and sectors, we especially welcome interdisciplinary perspectives, drawing on fields such as human resource management, organisational behaviour, information systems, operations and strategy, and the topic areas listed below.

This collection looks for work that is both novel and usable, research whose lessons carry from the study into other organisations. Contributions are welcome from experienced scholars, from practitioners writing from the field, and from doctoral and early-career researchers, who often see at first hand how generative AI is changing the manager’s job. What holds these together is a shared purpose, to sharpen how the field thinks about managerial capability under rapid technological change, and to improve how managers are actually developed.

The originality of this collection is its focus on development rather than description. Much current work maps how generative AI is changing managerial work and debates how far it should share in decisions (Kellogg et al., 2020); this collection concentrates instead on what managers now need to be capable of, and how those capabilities are built (Dixit and Jatav, 2024; Plotkina and Sri Ramalu, 2024). It also draws on organisations already working fluently with these tools, whose lessons have barely reached management development, and asks what the far larger number of managers in more established organisations can learn from them.

Consistent with the journal’s orientation towards practice, each paper is expected to demonstrate clear application beyond its immediate case and to translate its findings into guidance that those responsible for management development can implement. Contributions should establish not only what is changing in managerial work, but what managers must be able to do in response and how that capability can be built and assessed. Papers that combine analytical rigour with direct relevance to practice, and that offer transferable insight rather than isolated observation, are especially well suited to this collection.

The special issue also carries clear societal relevance, and aligns with three United Nations Sustainable Development Goals. As generative AI changes the capabilities managerial work demands, much of the workforce faces pressure to reskill (Chowdhury et al., 2024; McKinsey & Company, 2025, 2026; World Economic Forum, 2025); the issue addresses how managers are educated for that shift in line with SDG 4 on quality education. It attends to the quality of managerial work and the risk of overload as the pace rises, so that management stays effective and humane as more decisions are shared with generative AI, which speaks to SDG 8 on decent work. And it asks how organisations can adopt generative AI responsibly, treating the development of managers as what allows innovation to be introduced safely, in line with SDG 9 on industry, innovation and infrastructure.

Through this collection we hope to build a timely and practical account of one of the most significant shifts now facing managers, and to help shape how the next generation of managers, and those who develop them, are prepared for the work ahead.

GUEST EDITOR PERSPECTIVE:

The development of managers deserves fresh attention as generative AI reshapes their work. Much of the debate so far has been about the technology, what it can do and where its limits lie. The more pressing question for our field is about people: what managers now need to be capable of, and how we develop them for it. This collection is an invitation to put that question at the centre, and to build the evidence that management development will need as this shift continues. We invite contributions across the following five topic areas:

• Developing managers to make sound and accountable decisions with generative AI, including when to rely on it, when human judgement should prevail, and how to act when its outputs conflict with human values.
• Supporting managers to adapt to working with generative AI, sustaining their professional identity, confidence and sense of role, and building appropriate trust in what generative AI produces.
• Redesigning management development from one-off programmes towards continuous, embedded learning, and tailoring it to how generative AI reshapes managerial work differently across functions and sectors.
• Building and assessing the durable human capabilities that grow in value as generative AI is adopted, with evidence on how they can be developed.
• Developing managers to lead and decide responsibly across different cultural, national and institutional settings, where norms of accountability and acceptable use of generative AI differ.

Submissions Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available at: https://mc.manuscriptcentral.com/jmd 

Author guidelines must be strictly followed. Please see: https://www.emeraldgrouppublishing.com/journal/jmd

 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.

Key Deadlines

Opening date for manuscripts submissions: 30/09/2026

Closing date for manuscripts submission: 31/03/2027

Closing date for abstract submission: 01/12/2026

Email for submissions: A.huzooree@napier.ac.uk