Purpose&#xa0;of Review <p>To examine the current state-of-the-art in artificial intelligence (AI) applications relevant to trauma resuscitation workflows.</p> Recent Findings <p>AI is increasingly integrated into trauma care, supporting predictive modeling, team performance assessment, and real-time clinical decision-making. AI-enhanced tools span the full trauma resuscitation spectrum—from airway evaluation and ventilator management to hemorrhage control, neuromonitoring, and wound assessment. Computer vision and deep learning models can detect deviations in procedural technique, while video-based team analysis platforms improve non-technical skills such as communication and leadership. Emerging simulation environments adapt to trainee cognitive load, and prehospital triage algorithms outperform traditional scoring systems in acuity prediction and resource allocation. However, challenges remain around data governance, generalizability, clinician trust, and regulatory oversight. Model performance often degrades outside the original training environment, and limited availability of standardized, annotated trauma video datasets constraints development. Ethical deployment of AI models also requires transparency, site-specific validation, and careful medico-legal considerations.</p> Summary <p>AI holds transformative potential for trauma resuscitation, offering data-driven insights across clinical, technical, and team domains. From automated airway assessments to real-time video analytics of team behavior, these technologies are shifting trauma care toward more responsive, personalized, and performance-aware systems. While barriers to adoption persist, early successes demonstrate that AI can meaningfully augment, rather than replace, expert clinical judgment—positioning it as a powerful ally in delivering timely, high-quality trauma care.</p>