Employees reveal unexpected challenges of using AI at work
Organisations implementing artificial intelligence tools are losing nearly 40% of expected productivity gains to employees fixing low-quality AI outputs, according to research released by Workday.
The global study, which surveyed 3,200 full-time employees and leaders across North America, Europe, the Middle East and Africa, and Asia-Pacific in November 2025, highlights a significant gap between AI’s promise and its actual impact on workplace efficiency.
Workday found that while 77% of employees report increased productivity from AI over the past 12 months, roughly 37% of the time saved is being consumed by rework. For every 10 hours of efficiency gained through AI, nearly four hours are lost correcting, clarifying, or rewriting AI-generated content.
“For every 10 hours of efficiency gained through AI, nearly four hours are lost to fixing its output,” the report states.
“AI tax on productivity”
Heavy AI users face the steepest costs. Highly engaged employees spend approximately 1.5 weeks per year fixing AI outputs, creating what researchers describe as an “AI tax on productivity.” Only 14% of employees consistently achieve net-positive outcomes from AI use.
The burden falls disproportionately on younger workers and specific functions. Employees aged 25 to 34 account for nearly half of those experiencing the highest levels of verification and correction work. Human resources professionals bear a particularly heavy load, representing 38% of employees with the most AI-related rework.
“These employees tend to use AI frequently and with confidence, but they also report spending significantly more time auditing results,” the report notes.
Gaps in experience
A critical gap exists between leadership intentions and employee experience. While 66% of leaders cite skills training as a top investment priority, only 37% of employees most exposed to rework report increased access to training.
Fewer than half of roles in organizations have been updated to include AI-related skills, according to the study. In organizations struggling to achieve net productivity gains, less than 25% of roles are reported as AI-ready.
“AI has been layered onto roles that were never updated to accommodate it,” the report states.
Despite these challenges, the research identifies a successful model. Employees classified as “Augmented Strategists” consistently generate net productivity gains. Among this group, 93% treat AI as a tool to spot patterns rather than perform work for them, and 79% report increased skills training. Nearly all members of this group would recommend their organization as a place to work.
The study reveals a reinvestment problem. Organizations currently allocate 39% of AI cost savings to technology and infrastructure versus just 30% to workforce development. North American organizations are least likely to reinvest in people, with only 64% doing so compared with 84% in EMEA and 89% in APAC.
“Four in five agree that organizations that reinvest productivity gains into workforce development will be more competitive and resilient over the long term,” according to the research.
The findings suggest organizations should measure AI success differently. Rather than focusing solely on time saved, the report recommends tracking net value by accounting for both time saved and time lost to rework. Researchers advise updating job descriptions to clarify where AI assists and where human judgment is essential.
The research, conducted by Hanover Research, required all respondents to work full-time at organizations with at least $100 million in annual revenue and 150 or more employees. All participants were currently using or personally exposed to AI in their daily work.
