Dayforce warns workplace AI may erode skills by removing chances to learn

AI is taking over work that also taught people how to do their jobs, a new Dayforce report warns. In its survey of nearly 7,000 respondents across six countries, 65% said people in their organisations were losing the ability to perform some tasks that AI now handles—a warning about skills, not just jobs.

The learning hidden inside routine work

Dayforce calls the risk “experience debt”: a future cost in workforce capability when people lose opportunities to learn by doing. The report describes a tradeoff within automation. Removing repetitive work can also remove the repetition, context and exposure through which employees learn how more complex work gets done. The concern is not simply whether a task gets completed, but whether doing it still develops someone’s expertise.

The concern extends beyond individual tasks. Some 68% of respondents said organisations were losing important skills or expertise without fully realising it, while 73% said those capabilities were harder to rebuild. These are respondents’ assessments of workplace skills and risks, not independently measured declines or proof that AI caused them. The report’s warning rests on what people say they see happening around them.

Development competes with the day’s workload

AI is only one part of the fragility Dayforce describes. Experience debt can also accumulate when workloads repeatedly crowd out development or expertise stays with a small group rather than being shared. In the survey, 60% said understaffing had become normal in their workplace. That puts the report’s AI findings alongside a more immediate constraint: teams already struggling to make room for learning.

Knowledge was also becoming concentrated among fewer people, according to 54% of respondents. More than half said losing multiple key employees would cause significant or severe disruption. Those findings describe a related vulnerability: organisations depend on expertise held by particular people while facing concern about how that expertise will reach the rest of the workforce.

Dayforce chief people officer Amy Cappellanti-Wolf described repeatedly postponing development as a prioritisation decision, not merely a scheduling problem. Her argument is that future skills and leaders must be built while organisations deliver today’s work, rather than waiting for workloads to ease.

Who gets the time AI saves?

Respondents were not confident that faster work would create breathing room. Forty percent expected employers to assign more work if AI saved time on tasks. Another 39% expected slower hiring or reduced head count. Those answers describe anticipated employer choices, not staffing decisions already made or jobs already eliminated, as HR Dive’s coverage of the report makes clear.

Their hopes pointed in a different direction. Half wanted employers to use AI-saved time for more learning and development. That preference puts workforce development inside the decision about how to spend any efficiency gains, rather than treating training as a separate demand employees must fit around an unchanged workload.

Cappellanti-Wolf urged employers to reinvest some AI-created capacity in their workforce instead of focusing only on near-term efficiency. Her recommendation reaches beyond formal training: leaders should consider workloads, career opportunities and how people gain experience. The proposed response to experience debt is therefore not just more AI access, but a deliberate choice to reserve some of its gains for building capability.