A newly published perspective in the Journal of the Royal Society Interface argues that advances in AI, sensing technologies and modelling are transforming the study of collective animal behavior, with implications reaching far beyond biology, from robotics to the dynamics of human crowds.

A single ant has only limited information about its environment. Yet an ant colony can reliably discover efficient paths to food, adapt to obstacles, and reorganize when conditions change, solving problems no individual could manage alone. Understanding how such collective solutions take shape is a fundamental biological question, but also one with wide relevance: the same principles inspire swarm robotics, algorithms for complex optimisation, and even new ways of thinking about coordination in human crowds or cellular systems.

Collective animal behavior has become one of the most exciting meeting points of biology, physics, mathematics and AI, precisely because it asks how coordinated, adaptive behavior can emerge without any leader or central control. In their new perspective paper, “Future practices of interdisciplinary research in collective animal behavior,” Valentin Lecheval and Pawel Romanczuk argue that the current and future scientific questions of the field will require reshaping interdisciplinarity, with a tight integration of technologies such as automated tracking, AI and virtual reality with theoretical frameworks, and by an expanding range of systems under study..

Both authors are members of the Cluster of Excellence Science of Intelligence (SCIoI) at the Technical University Berlin, where intelligence is explored not only in individual brains, but as something that can emerge through interaction, from individuals to animal groups to other collective systems in nature.

Why this matters now

Valentin and Pawel argue that collective animal behavior is entering a new phase driven by new technologies, but also by the growing relevance of the field far beyond animal groups themselves. Collective behavior research has long been inspired by the idea of swarm intelligence: when many individuals combine their local decisions, the group as a whole can solve problems no individual could manage alone, like an ant colony optimizing foraging routes or allocating workers across food sources.

This “super-organism” perspective shows how complex, adaptive solutions can emerge from simple interactions. But today, the scale of what scientists can observe is changing substantially.

Automated tracking, drone recordings, AI-driven analysis and virtual-reality experiments now allow researchers to follow entire groups of animals in unprecedented detail, capturing patterns that were previously invisible. The next breakthroughs, though, will depend on more than just better tools. According to the authors, “The many challenging questions of collective behavior can only be tackled with multiple theoretical frameworks and novel empirical approaches,” which means that they will require deeper interdisciplinarity: shared concepts, comparable models, and a common language connecting the disciplines.

From animal swarms to engineered systems

The societal reach of these ideas is also growing. Principles from collective behavior increasingly inform swarm robotics, with applications expected within the coming decade, affecting issues such as environmental monitoring and agriculture to microplastics removal and search-and-rescue systems.

Similar approaches are being used to better understand collective cell movement in cancer, or to design buildings and exits that improve crowd evacuation. In this way, collective behavior is becoming not just a field about animals, but a broader framework for understanding coordination, intelligence and self-organization across living and engineered worlds.

The coming years will likely be shaped by this expansion, as new technologies open unprecedented windows into collective life, and interdisciplinarity becomes essential to making sense of it.

At a Glance

AI and new sensing technologies are transforming collective animal behavior research, enabling scientists to track and analyze whole groups in unprecedented detail.
Collective intelligence shows how complex, adaptive solutions can emerge without leaders, as seen in ant colonies optimizing routes or reallocating workers through simple local interactions.
The field is entering a new interdisciplinary phase, requiring shared concepts, comparable models, and a common language across biology, physics, mathematics, and AI.
Insights from animal swarms are increasingly shaping real-world applications, from swarm robotics and environmental monitoring to crowd evacuation design and cancer cell movement research.
Collective behavior is becoming a broader framework for understanding coordination and self-organization, spanning both living systems and engineered technologies.

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