Traditional job task analysis captures competence as a one-time snapshot, then typically waits 3-5 years to look again. In fast-moving fields, that lag lets credentials drift out of step with real practice. This session introduces the Dynamic Skills Surveillance System (DSSS): an always-on intelligence layer that continuously scans labor-market, regulatory, scholarly, and professional-association signals to detect emerging skills as they surface and flag obsolete ones for retirement. Combining NLP classification, an emergence-scoring algorithm, and subject-matter-expert validation at every decision point, the DSSS keeps credentials current, valid, defensible, and job-related. Framed within a Longitudinal JTA spanning entry to expert practice, it reimagines JTAs as continuous workforce intelligence rather than a periodic event, showing how AI and human judgment together keep assessment connected to the work people actually do as work continually changes.