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This study examines how employees’ exposure to coworker undermining may lead them to miss work deadlines. It offers a particular focus on the mediating role of diminished organization-based self-esteem and the moderating role of justice sensitivity in this connection.

The research hypotheses are tested with data collected among employees and supervisors who work in various industries.

Purposeful efforts by coworkers to cause harm translate into an increased propensity to fail to complete work on time, because the focal employees consider themselves unworthy organizational members. The extent to which employees feel upset with unfair treatments invigorates this process.

For employees who are frustrated with coworkers who deliberately compromise their professional functioning, diminished self-worth in relation to work and the subsequent reduced willingness to exhibit timely work efforts might make it more difficult to convince organizational leaders to do something about the negative coworker treatment. Pertinent personal characteristics can serve as a catalyst of this dynamic.

This study contributes to extant human resource management research by detailing the link between coworker undermining and a reduced propensity to finish work on time, pinpointing the roles of two hitherto overlooked factors (organization-based self-esteem and justice sensitivity) in this link.

The paper focuses on bridging the existing literature gap on the role of leadership in influencing employee engagement considering the advancement in technologies. With this, the author explores how the three critical elements of service-based companies' business environment-artificial intelligence (AI) success, employee engagement, and leadership are interlinked and are valuable for raising the engagement level of employees.

A purposive sampling strategy was used to select the employees working in the respective companies. The survey was distributed to 150 senior management employees but responses were received from only 56 employees making the response rate 37.33%. Consequently, an empirical examination of these 56 senior management employees belonging to service-based companies based in Delhi NCR using a survey questionnaire was conducted.

The PLS-SEM (partial least squares structured equation modelling) revealed that AI has a positive role in affecting employee engagement levels and confirmed the mediation of leadership. The magnitude of the indirect effect was negative leading to a reduction in total effect magnitude; however, as the indirect effect model has a higher R square value, the inclusion of a mediating variable made the model more effective.

This study contributes to extending the existing knowledge of the academicians about the relationship theory of leadership, AI implementation in organizations, AI association with leadership and AI impact on employee engagement. The author extends the theoretical understanding by showing that more integration of AI-supported leadership could enable organizations to enhance employee experience and motivate them to be engaged. Despite its relevance, due to the limited sample size, focus on a specific geographic area (Delhi NCR) and the constraint of only using quantitative analysis, the findings open the scope for future research in the form of qualitative and longitudinal studies to identify AI-supported leadership roles.

The study findings are beneficial majorly for organizations to provide them with more in-depth information about the role of AI and leadership style in influencing employee engagement. The identified linkage enables the managers of the company to design more employee-tailored strategies for targeting their engagement level and enhancing the level of productivity of employees. Moreover, AI-supported leadership helps raise the productivity of employees by amplifying their intelligence without making technology a replacement for human resources and also reducing the turnover rate of employees due to the derivation of more satisfaction from existing jobs. Thus, given the economic benefit and societal benefits, the study is relevant.

The existing studies focused on the direct linkage between AI and employee engagement or including artificial intelligence as a mediating variable. The role of leadership is not evaluated. The leadership enables supporting the easy integration of AI in the organization; therefore, it has an important role in driving employee engagement. This study identifies the contribution of leadership in organizations by providing the means of enhancing employee satisfaction without hampering the social identity of the company due to the integration of AI.