Persona Migration and Expectation Recalibration in Generative AI Adoption: A Longitudinal Study at a State Department of Transportation
3.80T1 sourcearXiv cs.HC
Source record
Published by arXiv cs.HC (T1 source). The original is at https://arxiv.org/abs/2607.13798.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryA longitudinal study of an eight-week Microsoft 365 Copilot pilot at a state Department of Transportation (n=124) found perceived usefulness declined significantly after hands-on use. Persona migration was substantial: 40% of Skeptics moved to Cautiously Positive while 68% of Champions shifted to less enthusiastic groups, indicating expectation recalibration rather than uniform adoption.
Why it mattersThe finding that enthusiasm drops after real use while skeptics cautiously upgrade reframes how to plan enterprise GenAI rollouts, supported by a concrete persona-tracking framework usable by adoption leads.
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