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Employee Satisfaction in AI-Driven Workplaces: Longitudinal Sentiment Analysis of Glassdoor Reviews for Future HR Strategy

Year: 2025

Type: article

Abstract: The rapid expansion of artificial intelligence (AI) in the workplace has reshaped job roles, yet its effect on employee satisfaction in AI-specific positions remains underexplored. We curated n = 1500 Glassdoor reviews of AI professionals (70% dated 2018–2025). We applied lexicon-based sentiment analysis (TextBlob) alongside R-driven statistical modelling to (1) quantify star ratings, (2) compare narrative sentiment with numerical scores, and (3) track annual sentiment trends from 2018 to 2025. AI specialists report high overall satisfaction (mean = 4.24) and predominantly positive sentiment (80.7%), although perceptions of leadership quality are consistently lower (mean = 3.94). Our novel AI-focused dataset and dual-analysis pipeline offer a scalable foundation for real-time HR dashboards. These tools can help organisations anticipate workforce needs, target leadership development, and implement ethical, data-driven AI practices to sustain employee well-being.

Source: Electronics

DOI: 10.3390/electronics14163180

Authors: Andrei Albu, Claudiu Brandas, Otniel Didraga, Gabriela Mariutac

Institution: West University of Timişoara

Language: English

Topic: AI and HR Technologies

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Decent work and economic growth

Open Access status: gold

Estimated APC paid: $2,896