EMS has been an underutilized strategic asset in healthcare systems since its inception in the 1960s. Similarly, the use of artificial intelligence has sparked controversy recently over its role in society and healthcare, specifically whether AI can be used to improve outcomes or streamline operations. EMS has an opportunity as a profession to capitalize on the advantages that AI can offer us in this new technological landscape. AI now provides practical levers for dispatch triage, dynamic deployment, documentation automation, and indeed clinical decision support, all of which can serve to reduce costs per unit, reduce response times, and improve downstream outcomes that will show hospital executives the true value of EMS (Weidman et al., 2025). 

The deployment of artificial intelligence (AI) in healthcare offers transformative potential for addressing global disparities, yet emerging startups confront substantial economic, regulatory, and operational hurdles. This analysis synthesizes evidence from peer-reviewed literature and policy reports, emphasizing issues such as eroding competitive moats, data fragmentation, regulatory complexities, clinician disengagement, value demonstration gaps, reimbursement uncertainties, and liability perceptions. With health tech investments reaching $29.1 billion in 2021, understanding these barriers is vital for fostering innovation (Chakraborty et al., 2023). Recommendations focus on strategic imperatives for startups to achieve sustainable integration. To capitalize on AI's potential, startups should prioritize interdisciplinary teams that blend technical expertise with domain knowledge in healthcare, enabling proactive barrier navigation and fostering resilient innovation ecosystems.