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July 20, 2026Information Technology and PeopleOpen Access

Generative artificial intelligence adoption and employees' perspectives on AI at work: toward unalienated working life or AI-augmented alienation?

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Authors

VRVisa RantanenKKKathrin Komp

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Overview

Rapid ethnographic case study explores AI technology adoption and employees' perceived social risks in a Finnish energy company, highlighting implications for acceptance.

Key Points

  • This study aims to understand employees' perspectives on AI's impact on job security and quality during technology adoption.
  • Rapid ethnographic case study conducted in a Finnish energy company during the introduction of a generative AI tool.
  • Analysis based on Marx's framework on alienation and improvisational change management theory.
  • Explored management of AI technology adoption and employees' perceptions of social risks.
  • Employees expressed concerns about job security and job quality in relation to AI adoption.
  • Rhetoric surrounding AI included both fears of alienation and potential benefits of reducing alienation through technology.
  • Employee initiative in technology adoption emphasized the importance of their acceptance for successful integration.

Cite This Study

Rantanen et al. (2026) studied this question.

synapsesocial.com/papers/6a5dbab98bd453d3397abde0https://doi.org/10.1108/itp-09-2025-1353
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1The promise of productivity or a source of anxiety? Employees’ perspectives on GenAI and workplace outcomes2026
  2. 2Adopting GenAI applications in the workplace: managerial implications and insights from ICT professionals2026 · 4 citations
  3. 3Humanizing GenAI at work: bridging the gap between technological innovation and employee engagement2024 · 35 citations
  4. 4Ready to Grip AI's Potential? Insights from an Exploratory Study on Perceptions of Human-AI Collaboration2024
  5. 5Employee Perceptions, Psychological Well-Being, and the Automation-Augmentation Paradox in the Age of Generative AI – A Qualitative Study2026