Why do workers feel confident with AI but get poor results?
Workers report high confidence using AI, but most say it fails on first attempt or takes longer than manual work. What explains this gap between perceived competence and actual performance?
WalkMe's AI at Work Pulse Survey, fielded June 10-20, 2026 by Propeller Insights among 2,037 working U.S. adults who use AI on the job, finds that "90% of employees feel confident using AI," but "only 24.6% say it works on the first try, and 50.2% say they have spent more time trying to get AI to do a task than the task itself would have taken manually." The report names this gap the "AI confidence trap": workers feel fluent, but the results frequently don't match. Confidence is highest, and most overstated, among the youngest workers — Gen Z self-reports 94.1% confidence and a 45% rate of "pretended to be more skilled with AI than they actually are," versus 13% for Baby Boomers, and a resulting work problem (a mistake, missed deadline, bad decision, or lost trust) for 31% of Gen Z versus 7% of Boomers.
WalkMe reads the gap as an adoption-support failure rather than a worsening honesty problem: year-over-year, "the share of employees who say they have pretended to know AI in a meeting dropped from 45.2% in 2025 to 28.3% in 2026," and passing off AI work as one's own fell from 48.7% to 32.5%. Its CTO KJ Kusch frames it as workers "becoming more comfortable," not more deceptive, while tools still fail to "meet people where the work actually happens." The report also cites two corroborating studies — SAP/Oxford Economics' Value of AI Report 2026 (2,600 business leaders, 13 countries), where 79% report rework, delays, or backlogs from low-quality AI output; and WalkMe's own State of Digital Adoption 2026 (3,750 enterprise workers/executives, 14 countries), where only 12% are fully confident AI understands their work's context and 9% trust it for high-impact decisions. Asked what would help, employees rank in-tool guidance and integration (33.7% and 30.2%) above separate training.
This is population-scale, self-reported evidence of the same split that Can self-ratings replace objective performance scores for AI competence? finds in a pooled correlation of literacy instruments: a confidence measure and a performance measure are "targeting different things." The WalkMe numbers don't replicate that finding directly — "works on the first try" is still a self-report, not a scored task — but the same split shows up at the level employees experience it: feeling capable with AI and getting a usable result on the first pass are not the same thing, and the gap between them is where the 50.2% "spent more time" figure originates.
The excerpt does not establish that AI use itself caused the lost time, the missed-deadline incidents, or managers' rising output expectations (51% report the latter) — all figures here are self-reported perceptions from a single pulse survey, not task logs or output audits, and the sample is restricted to workers who already use AI on the job, not a workforce-wide baseline. WalkMe sells an AI adoption and in-app guidance platform, and its headline recommendation — build guidance into the tools people already use — is also the product its survey implicitly argues for; that commercial interest doesn't make the confidence/first-try gap untrue, but it should discount how strongly the "in-tool guidance over training" conclusion is treated as disinterested.
Inquiring lines that read this note 12
This note is a source for these research framings, grouped by the broader line of inquiry each explores. Scan the bold lines of inquiry; follow any specific question forward.
How do AI-exposed occupations change in employment, wages, and skills? Does AI assistance erode cognitive skills while inflating perceived competence?- Why do most employees avoid higher-risk AI tasks despite having access to tools?
- Are heavy AI users different from casual users before they start using it?
- Why do the most diligent AI users report losing judgment fastest?
- Do younger workers overestimate their AI skills more than older workers?
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Can self-ratings replace objective performance scores for AI competence?
Do people's perceptions of their own AI competence match what they can actually do? This matters because assessment systems might rely on the wrong type of measure to evaluate workplace readiness.
same confidence/performance split, found here as a population-scale self-report gap rather than a scored-instrument correlation
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Does AI assistance help less experienced workers most?
When customer support agents gain access to an AI chat assistant, do productivity gains concentrate among newer, less skilled workers? Understanding this pattern matters for knowing who benefits from AI tools and whether deployment widens or narrows workplace skill gaps.
a measured-performance counterpoint from logged task data, against which this survey's self-reported "first try" figure can be read
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Why do developers keep using AI tools they don't trust?
Explores the paradox where AI adoption rises to 80% among developers even as trust in accuracy drops sharply to 29%. Why does usefulness persist despite frustration with unreliable output?
Evidence for A: Stack Overflow finds developer trust falling as adoption rises, echoing the confidence-versus-success gap
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Where does AI's time savings actually go in practice?
A survey of 3,200 AI users explores whether time saved by AI tools translates into real productivity gains or gets absorbed by correction work and task overload. Understanding this gap matters for predicting AI's actual workplace impact.
Evidence for A: Workday finds nearly 40 percent of AI time savings lost to rework, matching the slower-task finding
Related papers in this collection 8
Papers most semantically related to this note, ranked by cosine similarity in the embedding space.
- The AI Confidence Trap (AI at Work Pulse Survey)
- Beyond Productivity: Measuring the Real Value of AI
- Using AI More Does Not Reassure Workers, Managers Do
- Introducing Anthropic Interviewer: What 1,250 professionals told us about working with AI
- How AI Impacts Skill Formation
- What 81,000 people told us about the economics of AI
- From Junior to Senior: Allocating Agency and Navigating Professional Growth in Agentic AI-Mediated Software Engineering
- Anthropic Economic Index report: Cadences
Original note title
WalkMe's survey finds 90 percent of workers feel confident with AI while only 25 percent say it works on the first try