A new survey reveals 30% of employers plan to replace workers with AI in 2026, with IT and tech support roles among those at risk. The findings spark debate about job security and the limits of automation.
IT and technical support are no longer on the sidelines of the AI debate. They are moving to the center of it. A new survey of 1,250 U.S. business leaders finds that 30% of companies plan to replace employees with AI in 2026, and nearly half identify IT and technical support as roles most likely to be affected. Customer service leads the list at 54%, administrative or clerical follows at 49%, and IT and technical support comes in at 47%.
The same survey from AI Resume Builder notes that one in five employers already replaced specific roles with AI in 2025, which sets a clear baseline for what comes next. And the headline number is only part of the story.
Among companies anticipating AI-related job cuts next year, 59% expect to eliminate at least a tenth of their current workforce, and 10% expect half or more of roles to be replaced. The industries where leaders expect the most disruption include information technology, software, finance, energy, accounting, telecom, HR, manufacturing, retail, and others. This is not a distant scenario. It is an operating plan for the next budget cycle.
For IT and support teams, the automation targets are familiar. Ticket triage, knowledge base lookups, log parsing, meeting and document summarization, and routine research have long been treated as entry points for new hires. These are the same functions companies say overlap with AI’s current strengths. When those inputs move to AI systems, Tier 1 shrinks, and the remaining work concentrates in escalation queues where systems thinking and judgment drive outcomes. That is where the real friction will live, not in the marketing copy about productivity gains.
There is a second tension that has little to do with tools and everything to do with expectations. Most companies in the survey say AI is making employees more productive, and more than half expect people who use AI to produce more work each week. That sounds reasonable until you pair it with headcount reductions. If the same team is asked to absorb more complex escalations while low-complexity tickets are automated away, leaders will need to measure quality, not just speed. Mean time to resolution, error rates in automated actions, and rollback frequency will tell you whether the promise of efficiency holds up once it leaves the slide deck.
Workers are not powerless in this transition, but the advice has to be specific. The survey reports that two-thirds of leaders say employees with AI skills enjoy greater job security, and hiring plans favor candidates who can show real AI capability. In practical terms for IT, that means fluency with LLM-enabled ITSM platforms (and NLP), retrieval-ready knowledge bases, safe prompt and response patterns, and guardrails around privileged operations.
It also means being the person who can explain when an agent should act and when it should hand off, and documenting that boundary so it survives a shift change. Some job seekers are shifting their skills to enter the industry with the help of online AI courses.
The community response to these findings reflects deep anxiety about job security and the pace of technological change. Commenters have raised concerns about the broader implications of mass workplace automation, particularly for vulnerable populations already struggling economically.
The discussion extends beyond simple job loss fears to encompass questions about whether organizations are adequately considering the human and social costs of rapid AI adoption. Some observers have criticized the current state of HR practices, suggesting that if these roles are so easily replaceable, perhaps the profession itself needs fundamental rethinking.
The uncomfortable part remains. Even the teams that implement these systems may see their own roles redefined or reduced. That is not a contradiction. It is the nature of general-purpose automation. The real question is whether leaders will invest in the hard work that keeps systems reliable and people safe. Governance is not busywork. It is model selection, access controls, audit trails, rollback plans, and post-incident reviews that prevent a scripted fix from becoming a production outage. If those responsibilities are treated as optional, the cost of “efficiency” will show up somewhere else.
In a related news story, IBM planned some workforce restructuring. The CEO described the move as part of the company's AI-first strategy. That restructuring could automate many HR functions. AI agents would handle simple tasks like workforce tracking and employment verification.
The signal from the data is clear. IT and technical support are part of this next wave, with 47% of employers naming those roles as likely to be replaced next year. The response should not be panic. It should be ownership. Own the automation layer. Own the measurement. Own the handoff between agents and humans. If AI is going to reshape the help desk, the teams closest to the work should shape how it happens.
