Artificial intelligence as a catalyst for systemic sport ecology

Authors

Ugo Arbieu, Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Société Evolution, Gif-sur-Yvette, FranceFollow
Laís Carneiro, Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Société Evolution, Gif-sur-Yvette, FranceFollow
Sonia Tieo, Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Société Evolution, Gif-sur-Yvette, FranceFollow
Franck Courchamp, Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Société Evolution, Gif-sur-Yvette, FranceFollow

Author ORCID Identifier

Ugo Arbieu: https://orcid.org/0000-0002-0655-8756

Laís Carneiro: https://orcid.org/0000-0002-3828-7751

Franck Courchamp: https://orcid.org/0000-0001-7605-4548

DOI

https://doi.org/10.7290/jasm1766SS

Abstract

Artificial intelligence (AI) is reshaping both sport management and environmental science, yet these developments have largely evolved in parallel. AI can serve not merely as a technical tool but also as a catalyst for systemic sport ecology, a field that integrates sport, digital innovation and environmental sustainability. Advances in discriminative, generative and agentic AI enable the synthesis of complex ecological and sport-related data, improving monitoring, forecasting, resource efficiency, policy design, and decision-making across scales. In doing so, AI offers a pathway beyond fragmented sustainability interventions and can support holistic approaches to the interconnected crises of climate change, pollution, and biodiversity loss. However, the catalytic potential of AI depends on responsible implementation, equitable access to data, and attention to environmental costs. In short, AI can drive systemic transformations by enhancing the collection and integration of social-ecological data, fostering governance innovation and operational sustainability within the sport sector.

Recommended Citation

Arbieu, Ugo; Carneiro, Laís; Tieo, Sonia; and Courchamp, Franck (2025) "Artificial intelligence as a catalyst for systemic sport ecology," Journal of Applied Sport Management: Vol. 17 : Iss. 4.
https://doi.org/10.7290/jasm1766SS
Available at: https://trace.tennessee.edu/jasm/vol17/iss4/2