Office workers across Europe and the Americas have discovered a quiet advantage: artificial intelligence can make them look more competent than they really are. But this new edge is creating a dilemma for managers who must decide who deserves a promotion.
Research released on Tuesday by Use.AI, a platform that bundles multiple large language models into one subscription, surveyed 9,684 working adults in the US, UK, Canada, the EU, and Latin America. The findings paint a picture of delivered results running ahead of underlying skill.
More than half of respondents (52%) said AI had made them appear more experienced than they actually are. Nearly two-thirds (64%) admitted using AI to complete work they would not have been able to do independently, and 43% said it helped them take on responsibilities they did not yet feel qualified to handle.
The study also found that 35% of workers would struggle to perform parts of their current job without AI, and a quarter worried their employer believes they are more capable than they really are. Managers are often in the dark: 39% of workers said they had submitted AI-assisted work without mentioning it, and 30% had accepted praise for work the technology substantially produced.
None of this necessarily breaks any rules, since most workplaces have no disclosure requirement. But it does mean performance is being judged without knowing how much of the work was outsourced to a machine. The consequences reach into career progression: 19% said AI-assisted work had contributed to a promotion.
Should you tell your boss?
The obvious remedy—requiring employees to declare when they have used AI—is one that the company behind the research does not fully support. Ihor Herasymov, co-founder and CEO of Use.AI, told Euronews that mandatory disclosure of every interaction would quickly become impractical as AI becomes embedded in everyday software and routine work.
Instead, Herasymov proposes a narrower test: “The more useful threshold is whether AI materially shaped the substance of the work. If it generated a significant part of an analysis, recommendation, presentation, code or other consequential output, employees should disclose that assistance.”
The intent, he said, should not be surveillance but context. “It should give managers enough context to judge both the work and the human contribution to it,” Herasymov explained, adding that a workable policy should focus on material AI assistance, verification, and accountability, while making clear that the person submitting the work remains responsible for understanding and defending it.
How managers should measure performance
None of this establishes that those employees are unqualified—using AI skillfully is itself a professional skill that is increasingly relevant. The difficulty is that finished work no longer reveals what it once did about the person who produced it, which matters most when a company is deciding who is ready for more responsibility.
“Finished output still matters, but it is becoming a less complete measure of capability,” Herasymov told Euronews. “Employers also need to understand whether someone can explain the reasoning behind their work, detect flaws in an AI-generated answer, make decisions with incomplete information and respond when the technology produces something wrong or unexpected.”
He singled out one skill in particular: “Problem framing is particularly important. Can someone define the right question, challenge an assumption and explain why one course of action is better than another? That is much harder to infer from a polished final output alone.”
Few employers have solved performance assessment in the age of AI. “We do not yet see a settled model for assessing this. Organisations are still working out how AI should change performance and promotion decisions,” Herasymov said, adding that “the distinction between what someone can produce with AI and what they actually understand will become much more important in those decisions.”
Tool or crutch?
Asked whether the finding that 35% of workers would struggle without AI troubles a company that sells access to it, Herasymov did not dismiss the concern. “Yes, I think that finding deserves to be taken seriously,” he said.
“The concern begins when someone can produce an answer with AI but cannot reliably recognise when that answer is wrong, explain why it is appropriate, or make a sound judgment when the system has no reliable answer. At that point, the relationship starts to look less like augmentation and more like dependency,” he told Euronews.
He framed it as a trade-off rather than a verdict: “AI can make people faster and extend what they are able to do. But if those gains come with weaker independent judgment, that is a trade-off employers and technology companies should be willing to recognise and address.”
The technology is not standing still while employers work this out. According to data from METR, a US non-profit that evaluates AI systems, the time it takes for AI autonomy to double has compressed from an eight-month trend to just 4.7 months. The same compilation records a 1,400% year-on-year increase in AI's autonomous capabilities between early 2025 and early 2026, while access has expanded just as quickly. Downloads of AI tools rose from 15,000 to 11.8 million—a growth of 780 times—and publicly available MCP tools grew 35-fold to around 177,000.
As AI becomes more capable and more accessible, the line between human skill and machine assistance will only blur further. For managers across Europe, the challenge is not just to measure output, but to understand the human behind it. The rise of AI-written texts in parliaments and other domains suggests the phenomenon is widespread. The question is whether employers can adapt their assessment methods before the gap between perceived and actual ability becomes too wide to bridge.
