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Review | Open Access

The role of artificial intelligence in precision exercise nutrition: a shift from data to diets

Mohammad Nasba,b,c,1Ying Zhangd,1Ning Chena ( )
Tianjiu Research and Development Center for Exercise Nutrition and Foods, Hubei Key Laboratory of Exercise Training and Monitoring, College of Sports Medicine, Wuhan Sports University, Wuhan 430079, China
Rehabilitation Medicine Center /Tuina Department, Hubei Provincial Hospital of Traditional Chinese Medicine, Wuhan 430061, China
Affiliated Hospital of Hubei University of Chinese Medicine, Wuhan 430061, China
School of Physical Education, Hanshan Normal University, Chaozhou 521041, China

1 These authors contributed equally to this project.

Peer review under responsibility of Beijing Academy of Food Sciences.

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Highlights

• AI-driven insights enhance workout efficiency and recovery strategies.

• AI facilitates personalized diet plans based on genetic profiles.

• AI analyzes biomarkers to optimize macronutrient and micronutrient intake.

• AI tailors dietary interventions to individual athlete needs for peak performance.

Abstract

The integration of artificial intelligence (AI) in precision exercise nutrition is reshaping how athletes optimize their dietary intake for performance, recovery, and overall well-being. This article discusses the intersection of AI technologies in formulating precision nutrition strategies tailored to distinct physiological and metabolic requirements of athletes. AI-based mechanisms, such as real-time diet monitoring, continuous glucose monitoring, and nutrient optimization systems, offer unique insights into the impact of AI on advancing precision nutrition applications through the involvement in analyzing complex datasets, merging genetic, metabolic and environmental factors, thereby contributing precise dietary recommendations that adjust to evolving necessities of an athlete. However, the obstacles presented by AI in this domain, including ethical considerations, data confidentiality, and the necessity for uniformity across diverse populations are also confronted. By using AI, athletes can attain greater precision in their nutrition plans, ultimately enhancing exercise performance and promoting fatigue or injury recovery in ways that traditional methods cannot rival. This article further culminates with an address on future trends, emphasizing the role of AI in boosting precision nutrition engagement for athletes, even common exercise enthusiasts.

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References

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Food Science and Human Wellness
Article number: 9250623

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Cite this article:
Nasb M, Zhang Y, Chen N. The role of artificial intelligence in precision exercise nutrition: a shift from data to diets. Food Science and Human Wellness, 2026, 15(3): 9250623. https://doi.org/10.26599/FSHW.2025.9250623

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Received: 17 March 2025
Revised: 22 April 2025
Accepted: 19 May 2025
Published: 10 April 2026
© 2026 Beijing Academy of Food Sciences. Publishing services by Tsinghua University Press.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).