<p>Artificial intelligence (AI) is rapidly reshaping the ecological sciences, and invasion biology is no exception. From automated detection of invasive species to large-scale predictive modeling of invasion risk, AI has the potential to substantially change how we detect, forecast, and manage invasive species. Yet these same tools carry significant risks: technical limitations such as misidentification, hallucinations, and lack of vetting; ethical concerns about bias, equity, and reproducibility; and dual-use potential, in which tools designed to protect ecosystems might be exploited to promote activities that facilitate invasions. Here, I argue that invasion biology is uniquely situated at the crossroads of conservation, policy, and trade, making it both an early adopter and a high-risk domain for AI application. Drawing on recent advances in AI-assisted detection, big-data risk modeling, and hypothesis synthesis, I highlight the opportunities, risks, and dual-use dilemmas of AI in invasion science. I conclude with recommendations for responsible integration of AI, including transparent reporting, human-in-the-loop validation, and explicit consideration of dual-use potential when developing and publishing AI tools. Invasion biology, perhaps more than any other ecological subdiscipline, is well-positioned to contribute to shaping a responsible future for AI in environmental science.</p>