Athletic performance depends on technologies that can measure, model, and guide neuromuscular function across the complete athlete lifecycle. Robotics and Artificial Intelligence in Neuromuscular Performance provides an evidence-based framework for applying robotics, artificial intelligence, computer vision, wearable sensing, virtual reality, and biofeedback to assessment, training, injury prevention, rehabilitation, and return-to-play decision-making. Organized across 18 chapters, the book connects neuromuscular physiology with intelligent athlete systems, progressing from foundational concepts in computational biomechanics and robotic dynamometry to applied protocols for training load management, injury risk prediction, exoskeletal resistance training, smart rehabilitation, and AI-enhanced return-to-play clearance. Written for sports scientists, clinicians, physiotherapists, athletic trainers, strength and conditioning professionals, biomechanics researchers, and technology developers, it equips readers to evaluate rapidly expanding sports technologies with scientific rigor rather than assuming that innovation is inherently beneficial. Each chapter addresses validation status, measurement error, algorithmic limitations, data governance, and ethical risk, translating research evidence into criteria practitioners can apply directly. The AICICA framework, six implementation checklists, and integrated case studies extend the book beyond synthesis into practical guidance for responsible technology adoption in elite, clinical, and research settings.