The United Nations Development Programme (UNDP) and IEEE Humanitarian Technologies, part of the Institute of Electrical and Electronics Engineers (IEEE), are inviting teams of technologists and innovators worldwide to help three cities in Europe and Central Asia improve public transport planning, support energy efficiency investments and protect green spaces.
The GenAI for Good Challenge: Cities Edition will connect teams with municipal governments to co-develop and test responsible, open-source generative artificial intelligence (GenAI) solutions. Applications close on 13 December 2026.
Municipalities face complex challenges with limited resources. AI offers new possibilities, but many cities lack the staff, reliable data and technical expertise to identify where it can help and how to use it responsibly. The Challenge brings innovators and municipal teams together, with funding and expert support to turn ideas into prototypes and test them in practice.
Three cities, three challenges
Teams will develop solutions for urban challenges shaped by the green and digital transition:
- Pristina, Kosovo[1]: improving public transport planning. Develop a multilingual generative AI assistant to help municipal planners identify service gaps, improve connectivity and plan routes that respond to the city’s rapid urban growth.
- Rivne, Ukraine: supporting energy efficiency investments. Build an assistant that uses a building profile to guide users through cost estimates and financing options, and generate a shareable report to support investment decisions.
- Skopje, North Macedonia: safeguarding green infrastructure. Develop a solution that connects scattered records with the city’s digital Green Cadastre to inform decisions about urban green spaces.
The three cities were selected through CEF × AI, UNDP’s programme in Europe and Central Asia supporting municipalities to test, adopt and govern AI.
Support to build, test and deploy
The Challenge offers a structured pathway from an open call through a use case sprint, prototype development and piloting.
Nine teams selected for prototyping will receive US$10,000, with up to US$30,000 in additional funding for those chosen to pilot their solutions with a city. Participants will collaborate directly with city stakeholders, supported by technical mentorship from IEEE’s global network of engineers and experts, and UNDP’s development and public-sector expertise.
The initiative draws on UNDP’s City Experiment Fund (CEF), which works with cities across Europe and Central Asia to tackle complex urban challenges through strategic innovation, and BOOST, its regional impact acceleration programme supporting innovators. Up to three solutions will advance to city pilots, with open-source code and documentation to support municipal use and enable other cities to adapt and reuse them.
Part of a wider collaboration on responsible AI
The Challenge is one of the first initiatives under a wider collaboration between UNDP and IEEE Humanitarian Technologies on responsible, inclusive and human-centred approaches to digital transformation and AI. Beyond the Challenge, UNDP and IEEE will also explore cooperation on policy dialogue, capacity-building and institutional readiness for the responsible adoption, governance and use of digital technologies and AI. Areas of cooperation include technical cooperation and peer learning; engagement with technical experts, professional networks, academia, industry and civil society; and joint consultations, publications, learning products and knowledge exchange.
How to apply
Applications close on 13 December 2026. Teams must complete all required application components, including a technical assessment and a narrative proposal.
Explore the city challenges, eligibility requirements, upcoming Q&A sessions and apply: https://bit.ly/47XulHK
The CEF and BOOST are funded by the Ministry of Finance of the Slovak Republic through the Slovak Transformation Fund.
[1] References to Kosovo shall be understood to be in the context of United Nations Security Council resolution 1244 (1999).
