A scoping review argues that AI tools for diagnosing obstructive sleep apnea from snoring-related signals still lack sufficient evidence for clinical readiness. The coverage links the limitation to gaps in validation and performance reliability, noting that snore-derived acoustic biomarkers may be informative but are not yet dependable enough for care decisions. The review’s framing aligns with ongoing pediatric diagnostic challenges, where clinicians rely on objective sleep testing to differentiate mild disease and determine when interventions like adenotonsillectomy are appropriate. The net effect for the sector is a reminder that pediatric respiratory screening is high-stakes and that AI readiness depends on robust prospective evaluation rather than retrospective accuracy alone.