Narrative review explores resistance-training adaptation factors and AI's role in optimizing strength training.
The scientific foundations of sport-training methodology are commonly attributed to physiological principles; however, the extent to which these principles directly inform practical training models remains unclear. This narrative review examines the historical development of training theory—from early adaptology and integrative physiology to contemporary molecular discoveries in muscle biology—and evaluates their relevance to strength development. Strength expression is shown to be highly variable, influenced by neural, mechanical, technical, and psychological factors, challenging the traditional reliance on fixed percentages of maximal strength for training prescription. Additional complexities arise from individual response variability, performance plateaus, and the interference between molecular pathways activated by strength and endurance training. Emerging artificial intelligence systems offer new opportunities for individualized training optimization, injury prediction, and motor-learning analysis, while advances in brain decoding technologies highlight the potential role of willpower and cognitive processes in strength expression. Overall, current training methodologies remain heterogeneous and incomplete, although recent evidence increasingly supports modality-specific prescription principles based on load, contraction velocity, movement intent, and athlete training status. So, substantial research is required to more clearly connect physiological mechanisms with practical training applications.
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Cicchella et al. (2026) studied this question.
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