Empowering Government Agencies to Test, Refine, and Scale AI Solutions

The AI Learning and Innovation Hub Sandbox (AI Hub), led by Social Finance and HumanServices.ai, empowers government agencies to test, refine, and scale AI solutions tailored to workforce development and economic mobility. The AI Hub is launching in March 2025 with an initial cohort of four agencies.

Goals

• Develop foundational infrastructure for building AI competency and effective models for government agencies
• Offer a secure environment for agencies to experiment with AI tools tailored to their specific needs, regardless of their current AI readiness
• Share insights and learnings with public–sector leaders interested in using similar tools

If your agency is interested in participating in the AI Hub, fill out our form →

The Work

Social Finance, in partnership with HumanServices.ai, is building the AI Learning and Innovation Hub Sandbox (AI Hub) to help government agencies test, refine, and scale AI solutions. Ultimately, we hope the AI Hub will help improve service delivery and accelerate innovation while also helping underserved communities access economic opportunities more efficiently.

As it is built out over the course of 2025, the initiative will include: 

• Hands-on testing and sandboxing. In the AI Hub’s Sandbox, agencies will compare multiple AI solutions for a specific challenge using public or de-identified data. This hands-on approach allows agencies to assess the effectiveness, usability, and security of each tool in real-world scenarios, helping them refine their specific use case before procurement.
• Ethical framework development. The AI Hub embeds an ethical framework in all activities, providing guidelines and promising practices for responsible AI use. This includes addressing issues such as data privacy, algorithmic bias, and the creation of safe and effective systems.
• AI literacy and capacity building. The AI Hub will conduct regular workshops to improve understanding of AI concepts and applications among agency participants. These sessions will leverage expertise from academia, government, and the private sector to ensure that participants gain a well-rounded knowledge base.
• Shared learning. To further support broader adoption, all tested models and datasets will be shared through a centralized platform, providing insights into how AI tools perform across different use cases. This collaborative approach allows other agencies and stakeholders to learn from the testing process and consider how these solutions could fit their own needs. The work will continue to be updated, ensuring that new findings, improved models, and best practices are made available to all, fostering ongoing innovation and refinement.