This study examines how Artificial Intelligence (AI) is reshaping Human Resources (HR) with a specific lens on sustainability—people, planet, and profit—while addressing organisational realities such as declining cohesion, misallocation of human capital, weak performance oversight, role concentration, blurred professional boundaries, and the complexities of remote/hybrid work. A mixed-methods approach used (i) a survey (n=41) comprising 15 Likert type items across awareness, adoption, sustainability, and AI–sustainability integration; and (ii) qualitative inputs derived from an interview transcript focused on AI-enabled hiring at scale, bias, and explainability. The sample is predominantly 18–25 (83%), with female (59%) and sectors skewed to Education (32%) and Services (29%),indicating perspectives shaped more by awareness and aspiration than long tenure in large enterprises. Results show an awareness–adoption gap (Awareness agree=54% vs Adoption agree=39%). Despite moderate adoption, respondents express high confidence in benefits—AI reduces bias (74% agree) and improves productivity/engagement (68% agree). Sustainability appears valued—high perceived emphasis on inclusion and well being—yet measurement/reporting of sustainability metrics is underdeveloped. Respondents view AI as an enabler for tracking HR sustainability KPIs and aligning with ESG, but operational waste reduction and challenge-management are perceived as mixed due to implementation and governance barriers. We propose an AI-Powered Sustainable HR Model linking predictive analytics, NLP, ML, chatbots, and RPA to HR functions (talent acquisition, engagement, performance, L&D, and workforce planning), optimised across sustainability pillars (People–Planet–Profit) and measured via KPIs (satisfaction, diversity ratios, carbon reduction, retention, ESG scores). Practically, organisations should pair pilot-led adoption with robust governance (bias audits, explainability, privacy), capability building, and remote-work equity policies. Overall, AI in HR can deliver sustainable value when embedded within transparent, human-centred operating models.
Sathiyabama et al. (Tue,) studied this question.
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