David G. Collings, Trinity College Dublin

Jason L. Huang, Michigan State University

Dongyuan Wu, Fudan University

Patrick E. Downes, University of Kansas

This special issue examines how artificial intelligence, data analytics, and digital platforms fundamentally reshape talent management. Rather than treating technology as a support tool, it emphasizes technology as a central force that challenges traditional understandings of talent conceptualization, performance measurement, and value creation. The issue welcomes conceptual and empirical research on how technology influences talent identification, development, and deployment.

The call addresses three themes: how technology reshapes talent practices through AI-driven systems and remote work, ethical challenges such as bias and employee burnout, and the shift toward skills-based hiring. Organizations struggle to integrate technology into talent practices effectively and equitably, creating opportunities and risks that require scholarly attention.

Intended for human resource management and organizational behavior researchers and practitioners, this call seeks contributions advancing theoretical understanding of technology's role in modern talent systems while addressing practical concerns around implementation, ethics, and strategic coherence.

Appel publié par Human Resource Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How does technology reshape the nature of exceptional performance and how organizations define and measure high-performance and high-potential?
• What are the implications of technology for how individuals generate exceptional value in organizations?
• How does technology interact with employee KSAOs in the generation of exceptional value?
• How does technology alter the distribution and visibility of exceptional performance in organizations?
• What does agentic AI mean for the composition and performance of teams?
• Are traditional measures and understandings of high-potential still relevant in the context of emerging technological trends?
• How are companies using technology to shape talent-related expectations and outcomes?
• How do organizations design tech-enabled talent processes that shape the experiences of high-performing and high-potential employees?
• What role do digital tools play in fostering engagement, perceived justice, well-being, and retention of high-performing employees and individuals in pivotal roles?
• How do organizations adapt to ensure technological advancements enhance, rather than hinder, strategic talent strategies?
• How does technology reshape the role, authority, and activities of HR professionals in talent management?
• How can HR professionals play a leadership role and strike a balance between what technology can do and what technology should do in talent-related decision-making?
• How can organizations leverage AI and digital tools to reduce administrative burdens while improving talent outcomes?
• How do HR teams utilize efficiencies to focus on more strategic activities related to talent identification, development, and deployment?
• How can organizations manage the balance between technology and human judgment in talent management?
• How do companies integrate AI and automation without compromising the human aspects of leadership, decision-making, and talent evaluations?
• How does technology impact the emergence of expertise in organizations?
• How does technology impact the nature of performance distribution and the identification and management of critical roles in organizations?
• How can organizations transform their approaches to talent planning, attraction, and activation to address skill scarcity?
• What is the effectiveness of a skills-based hiring approach in recruiting talent for pivotal roles, and can rapid on-the-job training and reskilling better fill talent gaps?
• How do companies navigate skill gaps and talent reskilling in fast-changing industries?
• How does technology facilitate internal mobility and the dynamic recomposition of capabilities over time?
• How can digital platforms and algorithmic management enhance visibility into employees' skills and career aspirations?
• How can companies create and better utilize internal talent marketplaces to support career transitions and the allocation of talent to critical roles?
• What role does technology play in skills matching and identifying development pathways for high-potential employees in organizations?
• How can organizations effectively manage hybrid and nonstandard work arrangements as part of broader talent systems?
• What role does technology play in managing dispersed teams, ensuring productivity, and fostering collaboration among strategically valuable contributors?
• What challenges arise from integrating different employment models, and how can organizations optimize the experience and retention of talent across organizational boundaries?
• How can organizations ensure that talent continues to support the development of colleagues through knowledge transfer and mentoring in dispersed work contexts?
• How can organizations create talent systems that support experimentation with new tools and processes?
• What cultural and leadership factors influence an organization's ability to adapt to technological change in talent-related practices?
• How can businesses cultivate a mindset of continuous improvement and openness to innovation rather than resistance to change?
• How can organizations ensure that technology-enabled talent management promotes fairness, transparency, and inclusion while safeguarding ethical standards?
• How do organizations mitigate the potential that technology introduces bias into talent management, and how can organizations mitigate these risks?
• How can HR leverage AI and data analytics to drive more equitable talent identification, development, and deployment practices?
• How can organizations safeguard ethical principles related to privacy, transparency, data security, and algorithmic accountability in talent decisions?

Timeline

• March 1, 2027: Submission window opens
• March 31, 2027: Submission deadline