Bots and Bosses: AI's Impact on Managerial Job Satisfaction in India

Shobhanam Krishna (), Anita Choudhary (), Rohit Dwivedi () and Ashutosh Bishnu Murti ()
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Shobhanam Krishna: IIM Shillong
Anita Choudhary: IIM Shillong
Rohit Dwivedi: IIM Shillong
Ashutosh Bishnu Murti: IIM Shillong

Chapter Chapter 6 in Leveraging Emerging Technologies and Analytics for Empowering Humanity, Vol. 2, 2025, pp 103-128 from Springer

Abstract: Abstract Artificial Intelligence (AI) is reshaping the global workforce, eliciting optimism and apprehension. While concerns about job displacement, automation, and the diminishing value of certain professions are prominent, AI also presents opportunities to empower humanity by enhancing workplace efficiency and job satisfaction. Utilizing data from 500 managerial employees across various sectors in India, the paper conducted a regression analysis using SPSS version 26 to assess the impact of perceived AI integration on job satisfaction. The uniqueness of this paper lies in its comprehensive industry-wide analysis within the specific economic context of India, addressing multiple critical factors associated with AI integration. It offers insights into the strategic and operational impacts of AI technologies relevant to managerial decision-making and connects to concerns about the ethics and security of AI decision-making. The results demonstrated a significant relationship between perceived AI integration and job satisfaction, with the model accounting for 34.8% of the variation in job satisfaction. The findings indicate that perceived AI integration is associated with increased job satisfaction through enhanced AI-integrated organizational psychology. This paper adds to the existing literature on AI and job satisfaction by providing a detailed analysis in the Indian context for the first time.

Keywords: Artificial Intelligence (AI); AI integration; Cognitive AI; Decision-making; Ethical AI; Job characteristics theory; Job satisfaction; Regression analysis (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-981-96-8582-0_6

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DOI: 10.1007/978-981-96-8582-0_6

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