Applicants should be US based nonprofit organizations, but we encourage partnerships between multiple organizations including partnerships between nonprofits and for-profit startups, consultants and other technology experts. We encourage collaborations between nonprofits and technical experts.
Catalyzing transformative economic opportunities through advanced AI technologies.
Building on the success of our inaugural year, the GitLab Foundation is thrilled to announce the continuation and expansion of the AI for Economic Opportunity Fund with a second round of funding focused on demonstration and scaling.
This initiative represents a partnership between the GitLab Foundation, Ballmer Group, and OpenAI, demonstrating our collective commitment to leveraging emerging AI technologies to create economic opportunity and drive income growth.
Our Commitment
In this second year, the AI for Economic Opportunity Demonstration and Scaling Fund has evolved into a two-phase initiative:
In the first phase, the GitLab Foundation will grant a minimum of $3.5 million to up to 14 demonstration projects. These projects will be focused on developing and deploying prototype tools, gathering user feedback and building evidence of outcomes.
In the second phase, Ballmer Group will provide funding to scale high-potential projects, awarding either 1-year or 2-year grants ranging from $500K to $1.5M per year to a maximum of six selected grantees from the demonstration phase.
OpenAI will continue to provide both financial and technical support to grantees, including additional funding, access to early product releases, credits, and technical advice.
Additional funders are encouraged to participate in helping source, review and support these high potential projects. We expect total awards over the lifecycle of this funding round to exceed $10 million.
We are interested in creative applications including (but not limited to) tools and services that improve economic opportunity across many applications: skill development, job matching, hiring systems, internal mobility, coaching, benefits access, debiasing systems, data analysis and use, job quality, etc.