Glassdoor Report: AI Workplace Sentiment Plummets to 53% Negative by Mid-2026

A Glassdoor analysis of employee reviews from June 2025 through May 2026 reveals that worker sentiment regarding AI in the workplace has turned predominantly negative, with 53 percent of comments expressing criticism by mid-2026. This marks a sharp decline from 2019, when 81 percent of AI-related comments were positive, indicating a significant shift in how employees perceive AI's impact. For broader context, explore our AI News. For broader context, explore our Top 100 AI Tools.

Shifting Tides: The Rise of AI Criticism

The volume of US employee reviews mentioning AI, including specific terms like LLMs, GPTs, or OpenAI, surged by 240 percent year-over-year. This dramatic increase in discussion reflects AI's growing presence in daily work life. However, the nature of these discussions has turned predominantly negative. The proportion of positive AI comments has fallen sharply to 43 percent by mid-2026, while negative sentiment now represents the majority at 53 percent.

Primary Concerns: Job Loss and Workplace Impact

The most prevalent complaint among employees is the fear of job loss, which accounts for 20 percent of all negative comments. Beyond job displacement, criticism extends to several other areas:

• Forced Tool Adoption: Employees express dissatisfaction with being compelled to use new AI tools.
• Degraded Customer Experience: Concerns are raised about AI negatively impacting the quality of customer interactions.
• Workplace Surveillance: AI's role in monitoring and automated management messages contributes to feelings of alienation, cited in 10 percent of negative reviews.
• Unrealistic Productivity Expectations: Workers feel that AI implementation leads to unreasonable demands for increased output.

Varying Sentiment Across Roles and Demographics

Employee sentiment towards AI varies significantly across different job roles and demographic groups. Leadership roles generally exhibit the most positive outlook on AI. In contrast, specific professions show high levels of skepticism:

• Insurance Claims Workers: Up to 98 percent of comments from this group are negative regarding AI.
• Journalists: 81 percent of journalists' comments express negative sentiment.
• Software Engineers: Even within the tech sector, software engineers show skepticism, with 57 percent of their comments being negative. Software architects, however, tend to rate AI positively.

Demographically, Gen Z women emerge as the most skeptical group, with only 21 percent of their AI comments being positive. This contrasts sharply with Gen Z men, 42 percent of whom express positive sentiment.

Company Size and AI Perception

The Glassdoor analysis also reveals a correlation between company size and employee sentiment towards AI. Negative sentiment tends to increase with the size of the organization:

• Firms under 200 employees: 51 percent negative sentiment.
• Firms over 10,000 employees: 67 percent negative sentiment.

Conversely, positive reviews are categorized into two main groups: "AI winners," who constitute 44 percent of positive comments, and "well-supported AI users," making up 41 percent. These categories suggest that positive experiences often stem from perceived benefits or adequate support in AI integration.

Conclusion

The Glassdoor report highlights a critical shift in employee perceptions of AI, moving from predominantly positive to increasingly negative. While the adoption of AI tools like LLMs, GPTs, and OpenAI continues to grow, concerns about job security, forced adoption, and workplace surveillance are becoming more pronounced. This evolving sentiment underscores the importance for organizations to address employee fears and ensure thoughtful, supportive AI integration strategies to mitigate negative impacts and foster a more positive workplace environment.

Sources

• A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics
• GitHub - shashanksal/employee-review-analysis-ML: A machine learning project that uses a Glassdoor dataset for employee review analysis · GitHub
• Quantifying truth and authenticity in AI-assisted candidate...
• A comprehensive list of 2025 tech layoffs