The greatest threat to a tech worker’s job security may not be artificial intelligence (AI) but their lack of familiarity with it.
That is the overall takeaway from a comprehensive new study from Gallup: Tech workers who use AI less than once a month face an 18% risk of being laid off, triple the 6% risk seen by colleagues who leverage the technology on at least a monthly basis.
The stark divide highlights a growing AI literacy gap that extends across the broader U.S. labor market. While non-users across all combined industries face a higher layoff rate than active users (5% versus 3%), the disparity is nowhere near as severe as it is within the volatile tech sector.
The findings, drawing from a February survey of more than 23,000 American workers, persisted even after researchers controlled for variables like age, education, industry, and tenure.
The data reveals a striking paradox. Despite relentless headlines linking mass corporate downsizing to automated software, almost no displaced workers blame AI directly. Only 1% of recently laid-off respondents cited automation as the primary reason for their job loss. Instead, most pointed to traditional corporate explanations such as organizational restructuring, budget cuts, or role elimination.
However, employer-side tracking tells a completely different story. Outplacement firm Challenger, Gray & Christmas recently attributed roughly 40% of announced layoffs to AI integration. This disconnect suggests that restructuring is frequently a corporate euphemism for companies quietly shifting human responsibilities over to software platforms, leaving terminated employees unaware of the true catalyst behind their job loss.
Workforce analysts caution against a simplistic “use AI or get fired” narrative. Skeptics note that the data contains an inherent survivorship bias. Employees who proactively adopt AI tools tend to be inherently more adaptable, highly engaged, and positioned in fundamentally resilient roles—traits that have historically shielded workers from layoffs regardless of the specific technology used.
Whether AI fluency directly drives individual productivity or merely serves as a reliable proxy for employee agility remains an open question for corporate executives.
The broader labor market in early 2026 remains in a delicate state of cooling without collapsing. Approximately 21% of employees reported that their employers were downsizing in the first quarter of the year, a figure that has stabilized after a sharp climb that began in mid-2022. Conversely, a higher share of workers (34%) reported that their firms were actively hiring.
Ultimately, Gallup frames AI adoption not just as a personal career shield, but as a critical metric for organizational health. Tracking how AI tools are integrated across teams provides leadership with an early diagnostic tool to gauge how prepared their workforce is for the next wave of technological disruption. Non-users, meanwhile, will continue to face steep odds in an increasingly automated corporate landscape.
Kennith Jackson, senior vice president of AI solutions and operations at Andela, thinks a deeper shift is underway across tech. Companies aren’t simply reducing headcount, but are reassessing the skills, roles, and organizational structures needed in an AI-driven economy.
“U.S. tech companies last month announced the most employee terminations in almost two years, yet those same companies will be the biggest hirers,” Jackson said in an email. “The AI layoffs and future hiring surge tell the tale of AI transformation. As companies push towards becoming AI-native, they are reassessing the skills, roles, and organizational structures needed for the future. The result will not be a smaller workforce but one with a very different talent profile.”
“What should a software engineer do? Treat your skillset like infrastructure: continuously assess, maintain, and upgrade it,” Jackson added. “AI needs a human infrastructure layer and software engineers who take this approach are perfectly suited to fill this important function.”