Age-inclusive workplace practices tied to successful aging among older AI-sector workers

Older employees in AI-related workplaces report more successful aging at work when their organizations adopt age-inclusive human resource practices, according to a new study published in Current Psychology. The research, conducted by Xinyan Lv, Xiaoxing He and Dangchen Sui, found that these practices were significantly and positively associated with successful aging at work, and that the strength of the link depended on how actively employees engaged in a proactive behavior the authors call AI crafting.

The study drew on three waves of data from 236 older employees working in settings where artificial intelligence is integrated into the job. Using self-determination theory as its theoretical foundation, the researchers examined whether work-related basic need satisfaction served as the psychological pathway connecting organizational practices to successful aging at work. The three-wave structure allowed the team to test these relationships across separate points in time rather than from a single survey.

The reported results point to a consistent pattern. Age-inclusive human resource practices showed a significant positive association with successful aging at work. The relationship between those practices and work-related basic need satisfaction was stronger when older employees engaged more actively in AI crafting, the proactive behavior through which workers shape how artificial intelligence features in their own roles.

The model at the heart of the paper was a mediated moderation model. In this design, the researchers tested whether the interaction between age-inclusive human resource practices and AI crafting was indirectly associated with successful aging at work through work-related basic need satisfaction. Further analyses indicated that AI crafting did indeed moderate the relationship between organizational practices and successful aging at work via that need-satisfaction pathway.

In practical terms, the findings suggest that what an organization provides and what an employee does jointly matter. Age-inclusive practices were linked to better late-career outcomes, but that link appeared to operate more strongly when employees themselves took initiative in adapting to AI in their work. Neither organizational practice nor individual proactivity was examined as a stand-alone solution; the model positioned them as interacting forces.

The authors frame the study as an extension of self-determination theory into intelligent workplaces, where artificial intelligence is increasingly woven into everyday tasks. They also describe the work as a contribution to the literature on successful aging at work, identifying the joint roles of organizational practices and employee proactive behavior in supporting sustainable late-career development.

The paper’s abstract notes that the findings may offer practical insights for organizations seeking to support successful aging at work in the digital era. With the deep integration of artificial intelligence into the workplace, the authors identify the continuous adaptation of older employees as a critical challenge for organizational management, and position this study as an empirical step toward addressing it.

Subject of Research: Age-inclusive human resource practices, AI crafting and successful aging at work among older employees

Article Title: Age-inclusive human resource practices and successful aging at work: a mediated moderation model

Article References: Lv, X., He, X., & Sui, D. (2026). Age-inclusive human resource practices and successful aging at work: a mediated moderation model. Current Psychology, 45(21), Article 1654. https://doi.org/10.1007/s12144-026-10223-4

Image Credits: AI Generated

DOI: 10.1007/s12144-026-10223-4

Keywords: successful aging at work, age-inclusive human resource practices, AI crafting, self-determination theory, older employees, artificial intelligence, basic need satisfaction, mediated moderation, organizational management, Current Psychology, Age-inclusive, human