ustwo and the University of Bristol have launched PRISM, an open source plug-in that helps developers estimate the carbon impact of AI usage, bringing sustainability visibility directly into software development decisions.
ustwo, in collaboration with the University of Bristol, has launched PRISM, an open-source developer plug-in designed to help developers understand the estimated operational carbon emissions associated with AI usage during software development.
Integrated directly into the development environment, PRISM provides visibility into AI-related emissions, enabling teams to consider carbon impact alongside cost, speed and performance when making technical decisions. As AI adoption accelerates across organisations, the environmental impact of AI tools and workflows often remains hidden from developers. PRISM aims to address that gap by introducing sustainability as a development metric.
Released as a fully open-source project, PRISM is among the first open-source tools focused specifically on helping developers understand the estimated environmental implications of AI usage. The project allows developers and organisations to use, review and contribute to the tool, encouraging transparency, community participation and continuous improvement.
PRISM uses a transparent token-to-energy-to-carbon methodology informed by Green Software Foundation guidance and recent academic research to estimate the energy consumption and carbon emissions associated with AI usage.
“AI has become an everyday part of software development, but the environmental cost of using it remains largely hidden,” said Paolo Rizzi, Project Lead and Sustainability Principal at ustwo. “PRISM is our attempt to make that impact more visible and help developers and organisations make informed choices.”
Developed jointly by ustwo and University of Bristol software engineering students, PRISM provides directional estimates rather than precise carbon accounting. The creators say the tool offers practical environmental signals at the point where technical decisions are made, reflecting growing industry attention on responsible and sustainable AI adoption.
