This study examines HR practices in the Kumaun Division, Uttarakhand, India, and how individual competencies and organisational factors influence AI adoption and diversity management in resource-limited regions.
This study uses a concurrent mixed-methods design. Semi-structured interviews with 45 HR professionals were integrated with survey data from 234 practitioners in 28 organisations across tourism, education, government and NGOs. Multilevel modelling was used to analyse the nested quantitative data, complemented by a thematic analysis of the qualitative data. Integration was achieved through joint display and meta-inferences.
Organisational factors significantly explained the variance in AI practice effectiveness (ICC = 0.34; Level-2 pseudo-R2 = 0.43). Individual competencies accounted for substantial variance in diversity management outcomes (ICC = 0.28; Level-1 pseudo-R2 = 0.48). Cross-level interactions showed that organisational AI infrastructure moderated the relationship between individual AI confidence and practice effectiveness (γ = 0.19, 95% CI [0.02, 0.36], p < 0.05), whereas diversity policies amplified the effect of individual diversity commitment (γ = 0.23, 95% CI [0.08, 0.38], p < 0.01). Qualitative findings revealed that HR practices are shaped by material arrangements, cultural contexts and seasonal demands, including the emerging attention to neurodiversity.
This study provides actionable insights for HR professionals and organisations in regional contexts like Kumaun. HR practitioners must enhance AI literacy and cultural competence to integrate technology while respecting local diversity. Organisations should prioritise investment in foundational digital infrastructure and adopt mobile-first AI solutions to overcome connectivity barriers. Implementing formal diversity and inclusion policies will strengthen individual HR efforts and promote neurodiverse talent. Policymakers should support digital infrastructure development, subsidise AI training and foster regional HR frameworks for small enterprises. Together, these measures enable organisations to balance technological efficiency with inclusive, culturally responsive HR practices.
This study contributes to HRM-as-practice scholarship by providing an early multilevel examination of how HR professionals enact AI adoption and diversity management in the non-metropolitan Indian Himalayan context. This demonstrates how practice theory, multilevel modelling and intersectionality can be integrated to study HR work in resource-constrained emerging-economy settings.
