Towards ‘digital ecology’: Advances in integrating artificial intelligence from data generation to ecological insight

Abstract Ecology and artificial intelligence (AI) are becoming increasingly intertwined. Originally, the intersection between the two disciplines was driven by a critical need for AI to help process rapidly growing volumes of ecological data. Early applications primarily entailed applying AI methods to automate relatively basic tasks, such as detecting blank images from camera traps. However, researchers in both disciplines are beginning to recognize the potential for transformative advances when AI is fully integrated into ecological research and conservation practice. This special feature presents research at the cutting edge of the AI–ecology interface, focusing on work that advances the state of both fields beyond proof‐of‐concept to true interdisciplinary insight. The papers in this collection reveal a maturing field that balances technical advancement with ecological relevance. They address both methodological challenges and the critical need for meaningful integration between computer science innovations and fundamental ecological questions. As a whole, this collection demonstrates the potential for AI to enhance both fundamental ecological understanding and applied conservation efforts, as well as to bridge the gap between scientific discovery and policy implementation. The special feature underscores the importance of genuine interdisciplinary collaboration in developing technologies that not only showcase technical prowess, but also address pressing ecological challenges and support evidence‐based decision‐making in biodiversity conservation.