Artificial Intelligence: Species360’s Responsibility
September 2026
Wildlife conservation increasingly depends on data: records of how animals live, breed, age, and respond to their care and environment. As these datasets grow larger and more complex, they hold insights that can help us understand and care for species in ways that were not possible before.
Artificial intelligence (AI), when focused on conservation datasets, can be a powerful tool for finding those insights. Conservation scientists have used machine learning, a form of AI, for years: to identify species in millions of camera-trap images, to detect animal calls in acoustic recordings, and to predict where poaching is likely so rangers can focus their patrols.
It is also a technology whose costs to the environment, people, and our trust in information are real, unresolved, and growing.
Species360 will continue to evaluate and use AI where it improves animal care, species conservation, and the services our members depend on without undue costs or impacts, and to support humans making the decisions that matter.
A Globally Unique Resource
Species360's mission is to create globally unique insights so wildlife can thrive
The Zoological Information Management System (ZIMS) holds records on more than 22,000 species, contributed by more than 1,400 member institutions in over 100 countries, and our Species Conservation Toolkit Initiative (SCTI) provides population management tools (PMx, Vortex, and Outbreak) that conservation planners rely on worldwide. No comparable resources exist.
That scale carries a responsibility. Every welfare pattern we fail to detect, every breeding insight we leave buried, every conservation signal that goes unnoticed in this data is a missed opportunity for a species. If this resource can yield more insight, we have an obligation to find it.
Our Approach to Artificial Intelligence
AI raises legitimate concerns: its energy and water demands, its potential to replace skilled work and devalue human expertise, the security of the data it touches, its tendency to produce confident errors, and the concentration of power in the handful of companies that build it. We share these concerns and commit to responding to each of them.
We are equally clear about the potential. Species360 is both a conservation science and software organization, and advancing our technology is critical to our mission and our members. Where technology enables us to support our members responsibly, we have an obligation to do so transparently. Before we use AI capability for science, to build technologies or implement it in ZIMS, SCTI, or our services, we test it against the commitments set out below; if it fails, we pause.
For most of our 50+ year history, finding meaningful insights in data at the scale of ZIMS required resources beyond the capacity of Species360 or our membership. AI meaningfully increases that capacity.
In practice, that means work such as:
- Identifying unique insights in animal welfare and species demographics across the global dataset.
- Understanding how environmental or enclosure changes affect an individual animal or a population.
- Accelerating complex, data-heavy population management work.
- Integrating large datasets built to different standards.
- Translating our tools to bring the full value of Species360 to more regions of the world.
- Increasing team efficiency, especially in our product engineering teams.
We can do more for more species and advance our mission and our members’ goals.
If you’d like more information go how to become a Species360 Conservation Impact Partner, please contact giving@species360.org
Our Commitments
We asked our members what concerns them about AI, and their answers have shaped our commitments below. These commitments are not static, and we are committed to revisiting them as the technology, and our understanding of it, changes.
- Environment. We will seek to minimize the environmental impact of our AI infrastructure, prioritize cloud providers whose energy sourcing and approach to AI governance align with our mission.
- Human judgment. AI amplifies human expertise; it does not replace it. We will design our tools so that AI output informs decisions rather than makes them; allowing judgment and decisions to stay with the human professional.
- Our people. We will be proactively transparent when AI changes roles at Species360, and help staff adapt.
- Data ownership and protection. Member data belongs to member institutions, and we will not use it to train external AI models without their explicit agreement. Aggregate data derived from ZIMS remains under the oversight of our Board of Trustees, and any AI use of this data will go through our Board of Trustees and our internal data and AI governance processes.
- Quality and transparency. We will apply explicit quality standards to any AI-generated content or analysis published under the Species360 name, and say where AI was utilized to produce it. We own the quality of our services, whether human- or AI-produced.
- Equitable access. We will strive to ensure AI features support all members equitably, so every institution, including those with the fewest resources, can adopt and benefit from them.
- Independence from providers. We use commercial AI models and cloud infrastructure, but we will keep member data under Species360’s control, design our features so we can replace the underlying model, and not use a provider whose terms would compromise these commitments.
We are just beginning to understand what AI means for conservation: for our organization, for our members, and for the species we collectively care for. We do not have all the answers.
What we do have is a commitment to working through the hard questions openly, in partnership with the people this technology affects. We will say clearly which of our features use AI, what data they touch, and what safeguards apply, and we will be honest when our documentation has not yet caught up with the technology.
Questions and feedback: support@species360.org
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