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Talent management research today is increasing as organizational requirements attempt to meet the challenges of effectively managing talent to achieve organizations’ strategic agendas. However, in learning organizations specifically, investigations of talent management practices are limited, with this study exploring the role of talent management practices in employee satisfaction and organizational performance in Pakistan.

The study was conducted in various universities (public and private) in Pakistan using a quantitative approach. Cross-sectional data are collected through a questionnaire, with analysis and conclusions based on completed questionnaires from 403 respondents.

The study’s findings from the analysis by structural equation modeling (SEM) emphasize the positive and significant effects of most talent management practices (i.e. talent identification, talent development, talent culture and talent retention) on employee satisfaction and organizational performance (talent attraction is the exception). Employee satisfaction positively and significantly affects organizational performance and is found to have a mediating effect, bridging the relationships of most talent management practices (talent identification, talent development, talent culture and talent retention) with organizational performance.

The study’s findings support human resource professionals, academics and policymakers in managing talent practices to enhance organizational performance. The findings assist in developing core skills and talent-related competencies to achieve organizational goals and success.

The study fills the research gaps by developing a framework of talent management practices for employee satisfaction and organizational performance in learning organizations, which warrants further consideration.

This study aims to examine the relationship between self-perceived talent status (SPTS) and positive employee outcomes (work engagement and organisational commitment), mediated by organisational justice (distributive and procedural justice). The authors define SPTS as employees’ self-conceptualisation of talent, formed by inferring the organisation’s initiatives regarding training and development opportunities and through informal recognition by others.

The authors measured SPTS using eight items on a five-point scale. Through an internet survey company, the authors initially surveyed 1,207 full-time employees from 300 Japanese companies with ≥ 300 employees. In the second round of the survey, conducted after approximately two weeks, 876 (82.9%) responses were collected from the initial 1,207 respondents, which were used for the final analysis.

SPTS was directly and positively related to work engagement, organisational commitment, distributive justice and procedural justice. In learning organisations, SPTS was positively but indirectly related to work engagement and organisational commitment, mediated by distributive justice. In non-learning organisations, SPTS was positively but indirectly related to work engagement and organisational commitment, mediated by procedural justice.

Given SPTS’s positive impact on employee outcomes, to eliminate the information asymmetry between organisations and talent due to strategic ambiguity, organisations should increase SPTS by helping talents perceive the plethora of development opportunities in the talent pool.

The results demonstrate the utility of SPTS for improving employee outcomes based on strategic talent management (TM) mechanisms including talent rewards, talent development opportunities and promotions. Furthermore, the results demonstrate that distributive justice plays an important role in the build-based TM context of learning organisations.

Cloud computing, a dominant technology, significantly impacts organizations, necessitating talent management strategies for sustained growth. This study aims to explore the impact of cloud adoption on large French organizations through a “learning organization” perspective.

Interviews were conducted with business and IT stakeholders from 35 multinational organizations in France.

Cloud services have a high impact on large organizations, leading to a demand for cloud-related skills, a power shift from IT to business departments and increased shadow IT activities. Effective utilization requires organizational learning and a change management project, transforming organizations into productive and innovative learning organizations.

This paper contributes to cloud computing, organizational learning and talent management literature, offering managers a novel approach to handling cloud services.

The purpose of this paper was to identify talent development practices and processes that enhance professional and career growth of employees in South African higher education institutions (HEIs).

A quantitative study was carried out to investigate the subject matter. A structured questionnaire was used to collect the data from 265 academics in three South African HEIs. The Statistical Package for the Social Sciences, version 27.0, was used to analyse the data. Cronbach’s alpha coefficient and factor analysis were used to test the reliability and validity of the measuring instrument. Pearson’s correlations and regression analysis were used to interpret the relationship between the independent and dependent variables.

The results of the Pearson correlation test established a strong positive influence of training development, coaching and mentoring and career development on talent development. On the other hand, linear regression results indicated that training and development, coaching and mentoring and career development made a strong contribution to the model.

The scope of the study only applied to South African HEIs, making the generalisation of the findings to be limited because of the differences in an organisational context. Hence, future research should focus on different industries.

The study contributes to understanding how talent development can be leveraged to assist academics in HEIs to improve their professional and career goals. The findings suggest that HEIs must invest in talent development to help academics acquire the skills, knowledge and competencies required to perform their tasks.

This paper sheds more light on talent development practices and processes that enhance academic skills, knowledge and competencies in HEIs. Moreover, the study expands on the findings of prior studies concerning talent development in learning organisations.

The purpose of this review is to evaluate existing learning agility measures and offer recommendations for their use in organizational and scholarly contexts.

This is a general review paper assessing the psychometric qualities of prevalent learning agility measures. Measures were selected based on their predominance and use in the learning agility literature and organizational settings.

Learning agility measurement is an area requiring further research. Multiple conceptualizations of learning agility exist, making the true structure of learning agility unclear. The learning agility measures in the academic literature deviate from learning agility’s traditional conceptualization and require further validation and convergent validity studies. Commercial measures of learning agility exist, but their development procedures are not subjected to peer review and are not widely used in academic research, given the cost associated with their use.

Learning agility is prevalently used in organizational settings and is receiving increased scholarly attention. Various conceptualizations and measurement tools exist, and it is unclear how these theories and measures relate and differ. This paper contributes to practice by providing practical guidelines and limitations for measuring learning agility.

Learning agility was initially conceived as a multidimensional construct comprising people agility, results agility, change agility and mental agility. As the construct has evolved, the dimension structure of the measure has evolved as well. This study addresses a gap in our current understanding of how to conceptualize and measure learning agility.

Global talent shortages, new skill demand and rising numbers of unfilled posts are fuelling an increasingly challenging job market, exacerbated by economic uncertainty and transformational digital change. Seeking creative solutions in response, the authors examine talent management’s (TM) theoretical and conceptual foundations, specifically the identification and selection of talent and TM programme design to explore the challenges and benefits of side-of-desk projects as interventions.

Taking an inductive qualitative approach, questionnaires, focus groups and semi-structured interviews gathered data from three employee groups in a UK digital communications organisation.

The authors reveal inconsistencies in the definition and selection of talent, highlighting programme quality challenges to expose a direct correlation between participant experience and motivation and retention, along with the longer-term challenges of balancing talented human capital, shareholder expectations and sustainable workforce resourcing.

The authors' research extends existing knowledge concerning the effect of organisational culture, context and workforce demands upon TM programmes, providing theoretical and practical implications for leaders and policymakers in designing enrichment activities to motivate, develop and retain talent. The authors make recommendations to inform the future design of TM programmes, revealing new opportunities to develop hidden talent and presenting a realistic and sustainable toolkit for future practice in the form of an organisational logic model.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Cloud computing services provide firms with increased scope to grow and prosper. Successful adoption of cloud demands a focus on organizational learning and talent management to ensure that individuals, groups and units are equipped with relevant skills and capabilities needed to perform effectively in their roles as they evolve in the digital age.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The importance of learning in development in increasingly dynamic contexts can help individuals and organizations adapt to disruption. Artificial intelligence (AI) is emerging as a disruptive technology, with increasing adoption by various human resource management (HRM) functions. However, learning and development (L&D) adoption of AI is lagging, and there is a need to understand of this low adoption based on the internal/external contexts and organization types. Building on open system theory and adopting a technology-in-practice lens, the authors examine the various L&D approaches and the roles of human and technology agencies, enabled by differing structures, different types of organizations and the use of AI in L&D.

Through a qualitative interview design, data were collected from 27 key stakeholders and L&D professionals of MSMEs, NGOs and MNEs organizations. The authors used Gioia's qualitative research approach for the thematic analysis of the collected data.

The authors argue that human and technology agencies develop organizational protocols and structures consistent with their internal/external contexts, resource availability and technology adoptions. While the reasons for lagging AI adoption in L&D were determined, the future potential of AI to support L&D also emerges. The authors theorize about the socialization of human and technology-mediated interactions to develop three emerging structures for L&D in organizations of various sizes, industries, sectors and internal/external contexts.

The study hinges on open system theory (OST) and technology-in-practice to demonstrate the interdependence and inseparability of human activity, technological advancement and capability, and structured contexts. The authors examine the reasons for lagging AI adoption in L&D and how agentic focus shifts contingent on the organization's internal/external contexts.

While AI-HRM scholarship has primarily relied on psychological theories to examine impact and outcomes, the authors adopt the OST and technology in practice lens to explain how organizational contexts, resources and technology adoption may influence L&D. This study investigates the use of AI-based technology and its enabling factors for L&D, which has been under-researched.

T Education is a leading educational science and technology enterprise in China with technology-driven, talent intimacy and quality leadership as the core development objectives. Since its inception, it has been committed to creating better learning experience for children. As the predecessor of T-education, X-education was founded in Beijing in 2003. At first, it mainly provided after-school math counseling for school-age children. Over the past 10 years, its business has been expanding, covering almost every aspect of school-age education. This case studies accounting issues and business ethics challenges that firms may face when they transform from a single (traditional education) line of business to a multiple channel business.

The importance of mental wellbeing and the need for organizations to address it is increasing in the post-pandemic context. Although Artificial Intelligence (AI) is increasingly being adopted in HRM functions, its adoption and utility for enabling mental wellbeing is limited. Building on the Open System Theory (OST) and adopting the technology-in-practice lens, the authors examined the roles of human and technology agencies in enabling mental wellbeing.

The study was conducted in two stages; in Stage 1, the authors adopted a case methodology approach to examine the feasibility of a technology company's offerings to assess mental wellbeing. In Stage 2, the authors followed the grounded theory approach and interviewed 22 key stakeholders and HR leaders of diverse organizations. The authors used Gioia's approach to analyze the data.

The study demonstrates the interdependence and inseparability of human activity, technological capability and structured context. Specifically, the authors observe that AI adoption is pushing the boundaries of how organizations could support employees' mental health and wellbeing. These technological advancements and adoption are likely to facilitate the evolution of agentic practices, routines and structures.

This study carries two important implications. While the advent of cutting-edge technologies appears to affect employees' mental wellbeing, the study findings indicate the assistive role of technology in supporting mental wellbeing and facilitating changes in organizational practices. Second, the ontology of technology-in-practice shows how human–machine agencies gain newer relevance from the interactions that unite them. Specifically, per OST, technology (from an external context) can potentially change how mental wellbeing practices in organizations are managed. The authors extend the existing literature by suggesting that both human agents and internal contexts effectively limit the potential of technology agents to change existing structures significantly.

The authors address the need for more research on the technology-management interface, and the boundaries of technology-enabled wellbeing at work. While AI-HRM scholarship has primarily relied on micro-level psychological theories to examine impact and outcomes, the authors borrow from the macro-level theories, such as the OST and the technology-in-practice to explain how AI is shifting the boundaries of human and machine agencies for enabling mental wellbeing.