Artificial Intelligence (AI) and Human Resource Management (HRM) are together redefining the organisational strategies in the retail sector. The study titled “The Role of Artificial Intelligence in Shaping HR Strategies: Evidence from Retail in Jammu City, India” aims at finding how AI tools enhance HR practices such as recruitment, training, and performance management. The study has followed a mixed-method approach by combining interviews from HR managers (qualitative) and quantitative data from 150 retail employees in 20 retail stores from Jammu City, India. Data were analysed using a logistic regression model to find the impact of AI on HR efficiency, with variables including AI tool usage frequency, employee satisfaction scores, and turnover rates. A logistic regression model is employed to analyse the impact of AI adoption on HR efficiency, with variables including AI tool usage frequency, employee satisfaction scores, and turnover rates. The findings of the study suggest that AI-driven recruitment systems improve hiring accuracy by 32%, and predictive analytics reflect a reduced employee turnover of 18%. The limitation of the study includes the challenges related to data privacy concerns and resistance to AI adoption. The study shows the greater potential of AI in retail HRM in Jammu City, India, by contributing towards the existing literature review on AI in HRM ethically.

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The Role of Artificial Intelligence in Shaping HR Strategies: Evidence from Retail in Jammu City, India

  • Urvashi Thapa,
  • Aanyaa Chaudhary,
  • Hariom Gurjar

摘要

Artificial Intelligence (AI) and Human Resource Management (HRM) are together redefining the organisational strategies in the retail sector. The study titled “The Role of Artificial Intelligence in Shaping HR Strategies: Evidence from Retail in Jammu City, India” aims at finding how AI tools enhance HR practices such as recruitment, training, and performance management. The study has followed a mixed-method approach by combining interviews from HR managers (qualitative) and quantitative data from 150 retail employees in 20 retail stores from Jammu City, India. Data were analysed using a logistic regression model to find the impact of AI on HR efficiency, with variables including AI tool usage frequency, employee satisfaction scores, and turnover rates. A logistic regression model is employed to analyse the impact of AI adoption on HR efficiency, with variables including AI tool usage frequency, employee satisfaction scores, and turnover rates. The findings of the study suggest that AI-driven recruitment systems improve hiring accuracy by 32%, and predictive analytics reflect a reduced employee turnover of 18%. The limitation of the study includes the challenges related to data privacy concerns and resistance to AI adoption. The study shows the greater potential of AI in retail HRM in Jammu City, India, by contributing towards the existing literature review on AI in HRM ethically.