Startups Driving Artificial Intelligence Into Clinical Dermatology

Artificial intelligence (AI) is rapidly transitioning from innovation to routine clinical application in dermatology. This review examines how AI-enabled technologies are being developed and integrated across diverse clinical purposes and workflows. Using a structured assessment template, we analyzed international initiatives and industry-led innovations to identify the clinical gaps addressed, underlying technologies, use cases, and real-world implementation experiences. The resulting profiles highlight a broad spectrum of AI-driven and enabled applications, including wearable sensors with haptic feedback for objective symptom monitoring; patient-initiated teledermatology platforms that enhance access to specialist care; non-invasive diagnostic tools employing impedance spectroscopy; autonomous triage systems for dermoscopic lesions; and sensors that combine intrinsic skin biomarkers with exposome analytics. Collectively, these technologies illustrate a shift toward generating objective, reproducible data that complement clinical assessment, facilitating earlier detection, streamlined referrals, and longitudinal, patient-centred care. While validation studies are encouraging, regulatory and reimbursement pathways, along with limited data diversity, are current hurdles to a more large-scale adoption. By synthesizing insights from these technological approaches, this review aims to provide dermatologists with a pragmatic overview of AI-driven health technologies as emerging, evidence-based, commercial initiatives that may shape the future of dermatologic care.