Aqsa Shafiq1, Muhammad Aftab2.3.4* and Muhammad Mumtaz Ali5
1Department of Zoology, University of Okara, Pakistan 2Pathophysiology Department, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou, 450001, China 3Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, 450001, China 4State Key Laboratory of Esophageal Cancer Prevention and Treatment, Zhengzhou, Henan 450000, China 5 School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou 450001, China
*Corresponding author: maftab@gs.zzu.edu.cn
The rapid advancement of artificial intelligence (AI) presents transformative opportunities for the management of invasive species, a critical threat to global biodiversity, ecosystems, and economies. This review explores the integration of AI technologies—such as machine learning, environmental DNA (eDNA) barcoding, and predictive modeling—into the detection, monitoring, and management of invasive species. AI-based methods have demonstrated superior capabilities in early detection, offering faster, more accurate identification of invasive species than traditional approaches. These technologies enable predictive modeling that can forecast the spread of invasions, thereby enhancing the effectiveness of early detection and rapid response (EDRR) strategies. Additionally, AI-driven decision support systems and automated monitoring tools optimize resource allocation, making management efforts more efficient and effective. Despite these advancements, the deployment of AI in invasive species management presents significant challenges, including data availability, algorithmic bias, ethical considerations, and the risk of over-reliance on AI at the expense of traditional ecological expertise. The successful integration of AI requires addressing these challenges through interdisciplinary collaboration, ensuring that AI serves as a complementary tool that enhances human decision-making rather than replacing it. Looking forward, the role of AI in invasive species management is expected to expand, driven by ongoing technological innovations and the increasing need for global coordination in combating biological invasions. Future developments may include more adaptive AI systems capable of real-time learning, integration with other emerging technologies such as drones and bioinformatics, and a greater emphasis on ethical considerations and equitable access to AI tools. This review highlights the potential of AI to revolutionize invasive species management while emphasizing the importance of responsible and ethical deployment to protect ecosystems and biodiversity.