International journal of qualitative studies on health and well-being · 2025
Psychological impacts of AI-induced job displacement among Indian IT professionals: a Delphi-validated thematic analysis.
СтатьяОбзорНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Sharma Vinod, Deb Saikat, Mahajan Yogesh, Ghosal Avishek, Kapse Manohar
Аннотация
PURPOSE: This study investigates the psychological impact of Artificial Intelligence (AI)-driven job displacement among Indian IT professionals. It specifically explores how individuals psychologically experience the loss of roles due to automation, and how these experiences influence their emotional, cognitive, and behavioural well-being.
METHOD: A qualitative phenomenological approach was used to capture the lived experiences of 24 IT professionals who faced AI-induced job loss or reassignment. Data were collected via in-depth semi-structured interviews and analysed through thematic analysis. To ensure rigour and theoretical saturation, a three-round Delphi process involving 20 domain experts-spanning clinical psychology, organizational behaviour, and AI policy-was used to validate and refine the emergent themes.
RESULTS: Six core psychological themes were identified: emotional shock, erosion of professional identity, chronic anxiety and anticipatory rumination, social withdrawal, adaptive and maladaptive coping strategies, and perceived organizational betrayal. These themes reflect a multilayered resource loss, including identity, control, employability, and social belonging.
CONCLUSION: AI-driven role redundancy in the Indian IT sector is more than a labour market shift a deep psychological disruption. This study underscores the urgent need for organizations, mental health practitioners, and policymakers to develop anticipatory and compassionate interventions that can buffer the mental health consequences of technological transformation.
METHOD: A qualitative phenomenological approach was used to capture the lived experiences of 24 IT professionals who faced AI-induced job loss or reassignment. Data were collected via in-depth semi-structured interviews and analysed through thematic analysis. To ensure rigour and theoretical saturation, a three-round Delphi process involving 20 domain experts-spanning clinical psychology, organizational behaviour, and AI policy-was used to validate and refine the emergent themes.
RESULTS: Six core psychological themes were identified: emotional shock, erosion of professional identity, chronic anxiety and anticipatory rumination, social withdrawal, adaptive and maladaptive coping strategies, and perceived organizational betrayal. These themes reflect a multilayered resource loss, including identity, control, employability, and social belonging.
CONCLUSION: AI-driven role redundancy in the Indian IT sector is more than a labour market shift a deep psychological disruption. This study underscores the urgent need for organizations, mental health practitioners, and policymakers to develop anticipatory and compassionate interventions that can buffer the mental health consequences of technological transformation.