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1. What is the AI for Economic Opportunity - Demonstration and Scaling Fund?

   The AI for Economic Opportunity Demonstration and Scaling Fund is the third annual round of a groundbreaking philanthropic initiative to harnesses the power of artificial intelligence to improve economic mobility for millions.

   In just two years, the Fund has reviewed more than 650 applications and awarded 27 grants to organizations using AI to unlock benefits, deliver personalized career guidance, modernize workforce systems, improve benefits access, and expand access to education and employment. [See highlights of recent progress from past grantees here]

   In this round, we’re inviting bold proposals that show how AI can meaningfully transform the systems that shape economic opportunity. Examples include reimagining service delivery, unlocking new forms of personalized education and training, improving efficiency at scale, or creating entirely new ways to connect people with income, skills, benefits, and opportunity. We welcome both transformative approaches and incremental applications, so long as they hold the potential to drive lasting, meaningful change.

   Selected grantees will receive $250,000 in catalytic funding to prototype solutions and demonstrate progress, six months of cohort-based technical support from OpenAI engineers and other experts, API credits, and access to a network of leading practitioners and funders advancing AI for economic mobility. All awardees will also be eligible for a potential larger infusion of scaling grant capital through a number of philanthropic partners (more to be announced soon).

2. How does this year's grant opportunity differ from last year? This year's fund is very similar to last year, a two-phase initiative (demonstration & scaling) with increased funding and a focus on developing promising early prototypes and then directing additional capital, through funder partnerships and collaboration, at the highest potential projects.

We do anticipate announcing additional funding partners before the end of 2025 to increase the overall support for selected grantees, and having slightly more technically sophisticated support for grantees as part of our 6 month cohort process beginning in early 2026. 3. Who can apply for grants?

Applicants should be US-based nonprofit organizations, though the programs can be operating in non-US markets. 

We encourage partnerships between nonprofits and for-profit startups, consultants, and other technology experts. For-profit social enterprises will be considered on a case-by-case basis for mission alignment, with the opportunity to use a fiscal sponsor or nonprofit partner as an intermediary.

Related question: **Would the GitLab Foundation consider supporting a joint venture where a for-profit company based outside the U.S. partners with a U.S.-based NGO?** Yes. 

4. Can you share the concept note as a PDF? Sure! Here it is!

5. What types of projects are you looking for?

   We're seeking projects that improve economic opportunity for people with low incomes—whether by streamlining access to services and benefits, enhancing labor market matching, deploying personalized career guidance, implementing adaptive learning systems, improving public program efficiency, or overcoming language and accessibility barriers.

   We're especially interested in helping people who face the biggest barriers to economic mobility: those from low-income households, people without college degrees, and workers in low-wage jobs.

   We're eager to see transformative applications we haven't yet envisioned—but here are some high-potential areas we're particularly focused on:

   • Unlock and Harness Data for Impact: Build secure, privacy-preserving, and interoperable systems that unlock underutilized or siloed data, integrate across networks, and generate actionable evidence and insights to accelerate system-level change and economic opportunity outcomes.
   • Expand Agent Interoperability and Integration: Build orchestration layers, retrieval systems, and middleware that enable AI agents and models to effectively interface with institutional databases, user-level data, and external applications. We're interested in infrastructure that makes agentic AI systems practically deployable for economic opportunity outcomes—whether through multi-agent architectures, tool-calling frameworks, RAG pipelines, or API integration layers.
   • Make Services More Effective and Affordable: Design and deploy solutions that substantially reduce the cost per unit of service delivery while expanding reach, accessibility, and measurable improvements in outcomes. This includes platforms and tools that help training providers and service organizations rapidly develop, deploy, and scale high-quality programs with lower technical and operational barriers.
   • Empower Navigation Across Opportunity Pathways: Streamline access to education, training, and employment supports with tools and advising systems that guide individuals through complex choices at scale. We're particularly interested in multimodal interfaces, voice and visual navigation tools, and accessibility-first design that works across literacy levels, languages, and disabilities.
   • Advance Skills Validation and Mobility: Develop and scale registries, credentialing, and assessment tools that help workers gain validated skills and move more fluidly into in-demand jobs, unlocking pathways for economic mobility.
   • Personalize Learning and Support Persistence: Deploy intelligent tutoring, adaptive instruction, and other learning supports to measurably improve skill acquisition, persistence, and completion.
   • Strengthen Actionable Labor Market Intelligence: Enhance job market visibility and navigation through real-time, data-driven intelligence that connects workers, educators, and employers more effectively.
   • Build Employer Infrastructure for Skills-Based Hiring & Mobility: Help employers—particularly small and mid-sized businesses—identify, assess, and onboard nontraditional talent through skills-based hiring and internal mobility platforms, and systems that translate diverse credentials and experiences into hiring and mobility decisions.
   • Create Breakthrough Innovation Opportunities: We encourage high-leverage and high-potential solutions that expand opportunity, reduce systemic barriers, and create measurable gains in lifetime earnings. Wow us with your vision.

6. When are applications due?

   The first round of “concept note” applications are due on Oct 31, 2025, 5pm PST.

   Once these are screened, we will invite a full application from a select group on or before November 14, 2025. Full applications for finalists will be due on December 12, 2025.

7. What is the funding structure for this year? The fund has two phases:

   • Demonstration Phase (Feb - August 2026): GitLab Foundation will grant $250,000 to 16 demonstration projects. These project teams will also participate in a 6 months cohort based capacity development process and receive technical, financial and advisory support by OpenAI and other partners.

     These Demonstration grants are designed to support the critical early stages of development and proof-of-concept for promising AI applications that drive economic opportunity outcomes.

   • Scaling Phase (September 2026 and beyond): In the fund’s second phase, partner philanthropies will assess the highest potential projects for additional rounds of funding opportunities. More details to come.

8. When will awards be announced?

   Funding will be announced to grantees on or before January 30, 2026

9. How do we apply? Initial concept applications should be submitted using this form found on the main grant opportunity site. https://www.gitlabfoundation.org/futureofwork

   • You can find a template of the concept note here.

10. How will applications be evaluated?

    Applications will be reviewed by GitLab Foundation program officers, program advisors, select additional technical advisors including OpenAI engineers, as well as other funders.

    Our review will include an economic impact model (performed by GitLab Foundation staff) as well as a rubric that will include the following:

    • Organization / Team - Does the applicant or organization demonstrate strong operational capacity with a team that has the necessary skills to succeed in the proposed project?
    • Partnerships - Are they leveraging creative and strategic partnerships with key stakeholders such as governments, funders, companies, universities or other partners or networks to enhance the project's success?
    • Program structure & outcomes - Does the program have a well-defined structure that shows clear potential to deliver measurable outcomes benefiting low-income households or low-wage workers? (see GitLab North Star Overview)
    • Data Availability - Does the applicant demonstrate a strong understanding of relevant data sources, access protocols, and any compliance or privacy concerns? Do they have the necessary capabilities for data collection, management, and usage?
    • Outcome Scale Potential - Does the program show sufficient potential to scale to positively impact large numbers of individuals, and do the outcomes sufficiently meet ROI targets? (see GitLab North Star Overview)
    • Technical expertise: Does the applicant possess the necessary internal technical expertise, or have they clearly demonstrated the ability to collaborate with qualified technical advisors, partners or consultants to achieve the project goals?
    • Safety, Security, Bias and Ethics: Applicant has shown an awareness of relevant ethical or bias related concerns of the use of these technologies, and a reasonable plan for mitigation of those concerns.

    Unweighted rubric scores will be a primary factor, but not always the only factor, in moving an applicant from concept note to finalist selection. GitLab Foundation reserves the right to take risks on high potential or very unique projects with early stage teams, or other permutations that may be valuable to the overall desired outcomes that may further the mission of this project and our organization.

    Final applications will also be reviewed with this rubric, but final selection of awardees will also include our traditional due diligence as well as a priority ranking and review of a core set of advisors to ensure technical feasibility, outcome potential and other relevant success factors.

11. Can my organization submit more than one concept?

    Yes, but please limit to three submissions per applying organization.

    For large universities or institutions with a wide range of schools or departments we will consider more applications (i.e. treat each department or school independently). The intent of this limitation is not to limit the total number of inbound applications, but merely to encourage prioritization from applicants.

    Related Question: Did any of last year’s applicants have more than one concept note invited to the full application stage, or do multiple submissions mean an org is “competing against itself”? Answer: No, we typically will only bring one concept forward to a full application.

12. Is there any particular interest or concern about projects that might ultimately be headed for commercialization? No. Our focus is on the impact—specifically, the project’s contribution to positive economic opportunity outcomes—rather than on its business model. Commercialization or revenue generation can be effective paths to sustainability and scale, just as open-source, no-cost, or subsidized approaches can be appropriate in other cases.

13. Intellectual Property: What are the program’s expectations around openness and IP? Would we be required to open-source any components? You keep full ownership of your intellectual property. You don't have to open-source anything or share your code. You can choose whatever licensing model works best for you—whether that's commercial, open-source, or a mix. We encourage sharing insights, research findings, or data models when it helps increase equity or access or transparency, but it's not required.

14. How many applications did you receive during first two rounds? During our first round of these awards in 2023, ****we received 200 concept note applications, and over 450 during the second year in 2024. 27 demonstration grants have been awarded to date.

15. Can existing or future grantees of GitLab Foundation apply?

    Yes, we are treating the AI for Economic Opportunity grant decision process as a separate and distinct process. Being an existing grantee will not diminish your chances of selection.

16. What types of partnerships are encouraged for applicants?

    We encourage applicants to think creatively about partnerships that can strengthen their proposal. This is not mandatory, but these kinds of partnerships might include:

    • Technology Collaborations: If your organization lacks internal AI expertise, consider partnering with AI-focused technology companies, consultants or startups.
    • Nonprofit-For-Profit Alliances: Nonprofits may benefit from partnering with mission-aligned for-profits, particularly for product development and scaling.
    • Academic Partnerships: Universities and research institutions may provide rigorous evaluation frameworks, early technological innovation, data analysis, or AI expertise.
    • Local Governments and Public Agencies: Collaborating with government bodies can help scale services and ensure your technology solutions are aligned with public needs.
    • Funders and Investors: Explore co-investment opportunities with other funders to expand your project’s impact beyond our grant.

17. What is the grant award or project period?

    Grant contracts will be one year in length, but please be clear about the goals and outcomes you seek to achieve by the end of the 6 month demonstration phase (approximately Feb - July, with in person demo day tentatively planned for August or September).

    For the demonstration phase of this project, we value short cycle iteration and rapid learning that helps show achievement of milestones and progress.