According to Gallup's latest survey findings, tech workers who used artificial intelligence less than monthly faced triple the layoff risk compared to peers who used AI at least monthly. The research reveals a statistically significant correlation between AI adoption frequency and employment stability within the technology sector. Gallup's analysis suggests that regular AI use, not just role or sector, helped shape who kept their job during the layoff period. As reported by Gallup, "workers who are AI non-users appear to have been more vulnerable in the job market." The estimates are based on survey data in February involving more than 23,000 US workers, including 660 respondents who reported being unemployed after their jobs were eliminated. Gallup collected data on how often employed and displaced workers used AI — from daily to not at all — and then used a statistical model to estimate how factors such as AI-use frequency and industry were associated with the likelihood of job loss.
The survey data shows a clear pattern in AI adoption across different employment statuses. About 62% of laid-off workers reported using AI once a year or less, compared with 50% of currently employed workers. Meanwhile, 28% of employed respondents said they use AI frequently, versus 22% of those who had lost their jobs. Gallup called this gap statistically significant and noted that the pattern held after accounting for age, education, industry, and time since each layoff. The survey found that within the technology sector, the correlation between AI usage and job security becomes even more pronounced, with workers using AI less than monthly facing three times higher layoff risk than monthly users. The link between AI use and job security held even after accounting for factors such as age, education, and the sector in which one works. Among US tech workers specifically, the predicted probability of being laid off is about 6% for workers who use AI at least monthly, compared with 18% for workers who use the technology less often.
Technology workers already face significantly higher layoff risk compared to other sectors. Technology workers made up 13% of laid-off workers but only 6% of the employed workforce. Within the technology sector, the correlation between AI usage and job security becomes even more pronounced. As reported by Gallup, within technology, an industry already showing higher layoff exposure than other industries, workers who had not made AI a regular part of their work found greater risk. The survey revealed that across the wider workforce, the same link appeared, though weaker, suggesting that AI use is particularly protective in the technology sector. The findings indicate that AI adoption is becoming a fault line inside companies, one that's increasingly affecting individual careers, with employers already screening candidates for AI fluency. Even so, only about 1% of laid-off workers attributed their job loss directly to AI, with the most commonly cited reasons being organizational restructuring, cost-cutting and economic conditions. The data may "understate AI's indirect influence" in companies' layoff decisions, according to the researchers.
Gallup's Q1 2026 data reveals growing concerns about technology-driven job displacement across industries. 18% of US workers believe their job is somewhat or very likely to be eliminated within five years due to technology, AI, or automation, with that figure climbing to 23% among employees at organizations actively adopting AI. Within the tech sector specifically, 31% of workers harbor those fears, representing a significant increase from 15% in 2021 and 22% in 2024. Despite this concern, daily AI usage across the broader workforce still averages only 8-10%, with the heaviest users typically being leaders and those in white-collar or remote-capable roles. Between 38% and 43% of non-users cite data privacy and security concerns as their primary barrier, while another 36-46% simply prefer their current workflows. Frequent AI use at work has nearly doubled across tracked cohorts over the past two years, but the adoption curve favors those who already had digital fluency, organizational support, and job roles that naturally lend themselves to AI experimentation.
