International Journal of Human Resource Development: Practice, Policy and Research

Call for Papers

Special Issue: Human Capital Management, Development and Measurement in the Post-AI era: Reimagining the Value Proposition of HRM

International Journal of Human Resources Development, Practice, Policy, and Research (IJHRDPPR)

Guest Editors

Dr Wilson Wong (https://www.linkedin.com/in/wilson-wong1/)

Dr Prerna Tambay (https://www.linkedin.com/in/prernamoretambay/)

The Journal - IJHRDPPR

The International Journal of Human Resource Development Practice, Policy & Research is a peer-reviewed journal which seeks to bring together international practice and academic expertise to promote and support the understanding and practice of HRM and HRD.

It is a practice-centred journal, and it is aimed at synergising practice with theory and evidence to develop further insights. The journal is critically reflective and brings to light professional practitioners’ insight, ideas and understanding on the contemporary issues and challenges facing people management, its impact and influence.

The journal invites papers for peer review (approx. 7,500 words) AND perspectives articles (non-peer-reviewed) critically examining new and emergent practices in organisations and their impact on HRM, HCM and HRD. (approx. 3,500 words).

The latest issue can be found here - . https://reference-global.com/issue/IJHRD/10/1

Aim of the Special Issue

Advances in artificial intelligence (AI), automation, advanced analytics, and related digital technologies are reshaping the nature of work, organisational processes, and workforce capability. These developments have significant implications for how organisations manage, develop, and measure human capital and raise important questions concerning the future role of Human Resource Management (HRM) and Human Resource Development (HRD) in creating organisational and societal value.

Human Capital Theory has traditionally conceptualised employee knowledge, skills, and experience as critical drivers of economic productivity and organisational performance (Becker, 1964; Schultz, 1961). Similarly, Strategic HRM scholarship has long viewed human capital as a source of sustained competitive advantage (Barney, 1991; Wright & McMahan, 2011). However, the increasing integration of AI into knowledge-intensive activities, decision-making processes, learning systems, and performance management practices challenges established assumptions regarding capability development, expertise, value creation, and workforce contribution (Autor, 2015; Brynjolfsson et al., 2023).

At the same time, organisations are confronted with practical questions relating to workforce readiness, reskilling and upskilling, leadership, employee wellbeing, performance measurement, ethical governance, and responsible technology adoption. These developments create opportunities for both scholars and practitioners to re-examine existing frameworks and to develop new approaches to understanding, managing, and evaluating human capital in increasingly AI-enabled environments.

This special issue seeks contributions that advance theoretical, empirical, and practice-based understanding of human capital management, development, and measurement in the post-AI era. Consistent with the mission of IJHRDPPR, the special issue aims to foster dialogue between research, policy, and practice and welcomes contributions that demonstrate both scholarly rigour and practical relevance.

The special issue is guided by the following overarching question:

How should HRM and HRD rethink the management, development, and measurement of human capital to create sustainable organisational, social, and human value in the age of artificial intelligence?

Scope of the Special Issue

Submissions may address, but are not limited to, the following themes:

Human Capital and Organisational Capability

• The continuing relevance of Human Capital Theory in AI-enabled organisations
• Human-AI collaboration, augmentation, and capability development
• Strategic HRM and competitive advantage in digitally enabled contexts
• Interactions between human, social, organisational, and technological capital
• New perspectives on organisational value creation

Human Resource Development and Future Workforce Capability

• AI literacy and workforce preparedness
• Reskilling, upskilling, and lifelong learning
• Development of creativity, judgement, critical thinking, and adaptability
• Learning ecosystems and capability development
• Future directions for HRD theory and practice

Human Capital Measurement and Analytics

• Human capital analytics and people analytics
• Measuring workforce value and organisational capability
• Performance measurement in AI-enabled workplaces
• Metrics of innovation, resilience, learning, and adaptability
• Evaluation of (return on) investments in human and technological resources

Leadership and Organisational Transformation

• Leadership in AI-enabled organisations
• Talent management and workforce planning
• Organisational agility and dynamic capabilities
• Human-AI decision-making
• Organisational transformation and change

Responsible AI and Sustainable Work

• Ethical and responsible AI in HRM and HRD
• Employee wellbeing and meaningful work
• Fairness, transparency, and accountability
• Diversity, equity, and inclusion
• Sustainable workforce development and human flourishing

Types of Contributions

The special issue welcomes a broad range of contributions, including:

• Conceptual and theory-building papers
• Empirical studies employing qualitative, quantitative, or mixed methods approaches
• Systematic literature reviews and evidence syntheses
• Practice-informed research
• Organisational case studies
• Policy-focused contributions
• Academic-practitioner collaborative submissions

In keeping with the journal's commitment to integrating scholarship and practice, practitioner-oriented contributions should extend beyond description and provide critical analysis, evidence-based reflection, and implications for wider organisational practice and policy.

Submission Expectations

Submitted papers should clearly articulate:

• The significance of the research, organisational, or policy issue being addressed.
• The theoretical, empirical, or conceptual contribution of the work.
• The practical implications for HRM, HRD, organisational leaders, practitioners, or policymakers.
• The relevance of the contribution to understanding human capital management, development, or measurement in AI-enabled contexts.

Authors are encouraged to demonstrate explicitly how their work contributes to both academic knowledge and practical application.

Intended Audience

This special issue is intended for:

• HRM and HRD scholars
• Organisation and management researchers
• Human resource and learning and development professionals
• People analytics specialists
• Organisational development practitioners
• Consultants and advisers
• Business leaders and managers
• Policymakers and public-sector professionals

Submissions that bridge disciplinary, sectoral, or professional boundaries and contribute to ongoing dialogue between research and practice are particularly encouraged.

Submission Information

Manuscript submission deadline: April 30, 2027

Expected publication: September/ October 2027

Submission guidelines: Authors should follow the journal's standard submission requirements and indicate that their manuscript is intended for the Special Issue on Human Capital Management, Development and Measurement in the Post-AI Era.

Selected References

Autor, D. H. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29(3), 3-30.

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120. https://doi.org/10.1177/014920639101700108

Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. University of Chicago Press.

Boxall, P., & Purcell, J. (2016). Strategy and human resource management (4th ed.). Palgrave Macmillan.

Brynjolfsson, E., Li, D., & Raymond, L. R. (2025). Generative AI at work. Quarterly Journal of Economics, 140(2), 889-942.

Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company.

Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.8cd550d1

Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17(Winter Special Issue), 109-122. https://doi.org/10.1002/smj.4250171110

Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR analytics. The International Journal of Human Resource Management, 28(1), 3-26. https://doi.org/10.1080/09585192.2016.1244699

Minbaeva, D. (2018). Building credible human capital analytics for organizational competitive advantage. Human Resource Management, 57(3), 701-713. https://doi.org/10.1002/hrm.21848

Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation-augmentation paradox. Academy of Management Review, 46(1), 192-210. https://doi.org/10.5465/amr.2018.0072

Schultz, T. W. (1961). Investment in human capital. American Economic Review, 51(1), 1-17.

Stahl, B. C. (2021). Artificial intelligence for a better future: An ecosystem perspective on the ethics of AI and emerging digital technologies. Springer.

Wright, P. M., & McMahan, G. C. (2011). Exploring human capital: Putting "human" back into strategic human resource management. Human Resource Management Journal, 21(2), 93-104. https://doi.org/10.1111/j.1748-8583.2010.00165.x