Summary: Medical speech recognition goes beyond general ASR by handling clinical terminology, medications, dosages, abbreviations, specialty-specific language, and multi-speaker conversations. Ambient AI scribes raise the accuracy requirements further because transcription errors can affect downstream clinical documentation. Healthcare organizations should evaluate systems using clinical WER, medication and numerical accuracy, speaker attribution, security, and documentation quality—not overall WER alone. A clinical-grade architecture combines vocabulary adaptation, context awareness, validation, confidence scoring, secure processing, and clinician review to support accurate and reliable healthcare workflows.