KPMG Gen Z Interns Expect 33% Job Automation, Yet Feel AI-Ready

Of the 361 KPMG winter interns surveyed in February and March 2026, 78% said they felt at least somewhat prepared to work alongside AI in a future professional role, even as they expected roughly one-third of their future work to be automated or AI-enhanced. The tension between those two numbers is the defining signal in the firm's 2026 Winter Intern Pulse Survey, released March 25.

The survey spanned KPMG's Tax, Audit, Advisory and Business Process Group functions, with respondents identifying as 94% Gen Z and 6% Millennials. The automation expectation was not speculative: nearly 30% of interns' current assignments already involved some level of AI assistance, meaning the readiness question was grounded in lived experience rather than abstract concern.

Derek Thomas, National Partner-in-Charge of University Talent Acquisition at KPMG U.S., characterized the generational stance as deliberate rather than passive. "Gen Z isn't waiting to be told how to feel about AI, they're already looking for ways to stay one step ahead of it," he said. "They recognize that some entry-level work will be automated. What's different from prior technology shifts is how they respond: by doubling down on judgment, creativity and adaptability — the skills AI can't replace."

Beyond readiness, the survey surfaced a compensation expectation with direct implications for recruiting: interns anticipated a roughly 9% premium in entry-level pay for candidates with demonstrable AI skills. In a firm where offer competitiveness against other Big 4 players is a perennial pressure point during campus season, that figure gives talent acquisition teams a concrete benchmark.

For people managers, the findings identified a structural gap worth closing before the next intern cycle. With nearly 30% of current assignments already touching AI tools, interns arrive expecting real exposure, not simulated exercises. The survey's guidance called on Learning and Development teams to embed supervised AI-use labs covering prompt engineering, model validation and result interpretation into internship curricula. It also directed managers to assign work requiring genuine human judgment, such as synthesizing AI outputs into client recommendations, rather than tasks that amount to mechanical execution.

Campus recruiting teams have a parallel mandate: calibrate offer messaging around the 9% premium finding and position early-career AI upskilling pathways as part of the firm's value proposition to candidates who already expect AI fluency to carry financial weight.

Several forward-looking signals accompanied the release. Watchers should track updates to intern curricula, internal Learning and Development campaigns tied to KPMG Clara, KPMG Workbench and KPMG Private, and any revisions to entry-level compensation frameworks that link pay to demonstrable AI skills. The survey framed those as the likely next moves: KPMG leaders, per the findings, intend to use this data to refine early-career pipelines and accelerate competency frameworks for AI-augmented work.

For a firm where AI tools are already embedded at the engagement level in audit and advisory, the intern data points to a pipeline that is more prepared than skeptics might assume, and one that will raise the bar for what a competitive early-career offer needs to include.