Siegel Family Endowment Inc.

Siegel Family Endowment's giving philosophy treats philanthropy as society's risk capital — a framing shaped directly by founder David M. Siegel's background co-founding Two Sigma, one of the world's premier quantitative investment firms. Where traditional funders deploy capital reactively, Siegel takes a systematic, hypothesis-driven approach: staff identify a research question about technology's impact on society, fund organizations that generate evidence, and apply findings to subsequent grant cohorts. This inquiry-driven model, borrowed explicitly from the scientific method, means grantees are expected to be knowledge contributors, not just program executors.

The foundation's singular mission — to understand and shape the impact of technology on society — organizes giving across three pillars: Learning (building learner-centered education ecosystems with future-ready competencies), Work (ensuring workers shape how AI transforms employment and job quality), and Infrastructure (community-driven governance of digital, social, and physical systems). Grants across all three pillars appeared in each of the foundation's three 2025 cohorts, indicating roughly equal strategic weight.

Siegel explicitly favors proximate leaders — founders and practitioners who come from and represent the communities they serve. This commitment is not rhetorical; recent grantees span community-based organizations in Birmingham, rural innovation hubs, and workforce training programs serving workers in AI-disrupted industries. Alongside these smaller grantees sit MIT, Carnegie Foundation, and the Obama Foundation — indicating Siegel's portfolio spans grassroots to institutional anchor at once.

The most operationally significant feature of Siegel's model is staff-authored proposals. Foundation staff write the grant narratives themselves, eliminating the proposal-writing burden for smaller organizations and structurally ruling out cold applications. The foundation does not accept unsolicited proposals, has no grant portal, and does not publish open deadlines or RFPs. Grants are awarded on a rolling basis following internal review.

Relationship progression follows a loose arc: foundation staff identify potential grantees through convenings, field research, and peer referrals; they conduct exploratory conversations; they draft proposals internally; they present to the board for approval. First-time grantees typically enter through the annual AMA webinar (315+ attendees in February 2026), sector convenings, or referrals from existing grantees. Typical grant tenure runs multi-year, with renewal common for organizations that engage actively as thought partners and contribute to Siegel's public knowledge base.

Siegel's financial trajectory over the past decade is remarkable. The foundation was capitalized in FY2012 with a $43 million contribution from David Siegel, and total giving that year was just $154,337. By FY2024, the foundation held $568.1 million in assets and paid $27.8 million in grants — a near 300x increase in annual grantmaking over 12 years. Net investment income in FY2024 reached $92.5 million, driven by Two Sigma's management, with investment yields substantially exceeding annual giving in every year on record.

Annual grants paid have grown steadily across every available data point: $93K (FY2012), $1.1M (FY2013), $2.1M (FY2014), $4.5M (FY2015), $18.4M (FY2019), $22.3M (FY2020), $24.5M (FY2021), $24.8M (FY2022), $26.9M (FY2023), and $27.8M (FY2024). The FY2023 total giving figure ($33.9M) exceeded FY2024 ($27.8M), likely due to timing of multi-year pledge payments rather than a strategic pullback.

Public grant announcement data suggests the foundation's disbursement pace is accelerating. In calendar year 2025 alone, three announced cohorts totaled approximately $44.6M: $12M (May), $17M (July), and $15.6M (December) — exceeding any prior single fiscal year's reported grants paid and indicating either significant FY2025 growth or multi-year pledge structures bridging fiscal years.

Typical grant sizes based on publicly disclosed awards run $150,000 to $1,000,000 for most grantees. Large anchor grants include MIT's Learning Initiative ($15M multi-year), Carnegie Foundation for the Advancement of Teaching ($1.5M, 2025-2027), and Center for Democracy & Technology ($500K, 2024-2026). The December 2025 cohort distributed $15.6M across 31 organizations, implying an average of roughly $503,000 per grantee — consistent with the disclosed range.

By focus area, Education-adjacent grantees appear in every cohort and likely represent the plurality of grant dollars, consistent with the foundation's historical emphasis on K-12 transformation and CS education access. Workforce and Infrastructure grantees appear in roughly equal proportion, each accounting for an estimated 25-35% of remaining dollars per cohort. A smaller Chairman's Initiative allocation covers philanthropic-sector and cultural priorities and has appeared in prior 990 filings. Geography skews toward national-scope organizations in major metros but has expanded meaningfully to rural and community-centered contexts in 2025.

The table below compares Siegel Family Endowment to its asset-peer cohort — five foundations in the $560-$575M range, all classified as private grantmaking foundations (NTEE T20).

Among these peers, Siegel distinguishes itself in three respects. First, its mission thesis is far more sharply defined — technology equity across learning, work, and infrastructure — while peers maintain broadly defined or diffuse giving with no analogous inquiry-driven methodology. Second, Siegel's $27.8M in annual giving represents the clearest and most consistently published payout ratio in the cohort (~4.9% of assets), with three public grant cohort announcements per year providing unusual transparency for a family foundation. Third, Siegel's knowledge infrastructure — research fellows, quarterly grant cohorts, public AMA webinars, and published field insights — is substantially more sophisticated than standard family foundation operations at this asset level, reflecting the quantitative, evidence-driven culture of its Two Sigma origins.

Siegel was among the most active foundations in the technology-equity philanthropy space during 2025. Three public grant announcements — May ($12M), July ($17M), and December ($15.6M) — totaling approximately $44.6M, marked a significant increase over prior fiscal-year giving levels and established three-cohorts-per-year as the foundation's new operating rhythm.

The July 2025 round's $17M outlay to 15+ organizations was the foundation's largest single-cohort announcement on record. Named grantees included the Obama Foundation, Jobs for the Future, Carnegie Foundation for the Advancement of Teaching ($1.5M, 2025-2027), Harvard Law School's Center for Labor and a Just Economy, Center on Rural Innovation, Black River Innovation Campus, Aspen Digital, and Stanford d.school — a mix of national institutional anchors and emerging community-based organizations.

In September 2025, the foundation named its 2025-2026 Siegel Research Fellows cohort — practitioners and scholars working at the intersections of technology, labor, and governance — institutionalizing a knowledge-building infrastructure layer alongside direct grantmaking.

On February 5, 2026, President Katy Knight, SVP of Grantmaking Joshua Elder, and SVP of Research John Irons hosted the annual AMA webinar with 315+ participants and addressed 60+ questions about 2026 strategy. Leadership has been stable across all 2025-2026 public communications, with no signals of executive transition. The Learning/Work/Infrastructure framework continues as the organizational spine, with no major strategic pivots announced for 2026.

The most important insight about Siegel Family Endowment is that the conventional grant application does not exist here. There are no RFPs, no portal, no posted deadlines, and no unsolicited proposals accepted. Attempting to cold-submit materials will not advance a candidacy and signals unfamiliarity with the funder.

Attend the annual AMA webinar. Held each February and free to join, this is Siegel's most explicit public-facing engagement channel. The February 2026 session drew 315+ participants and addressed 60+ questions. Register early, attend live, and ask a substantive question that demonstrates genuine alignment with their research questions — not generic interest in funding. This is the clearest entry point for unknown organizations.

Subscribe to Siegel's insights publication and read strategically. The foundation publishes research questions, grantee spotlights, and field analyses at siegelendowment.org/insights. Staff expect potential partners to be familiar with the foundation's current thinking. Reading recent publications before any outreach is a baseline requirement, not optional preparation.

Use their vocabulary, not yours. Siegel operates through the framework of inquiry-driven grantmaking, proximate leadership, future-ready competencies, and community-centered infrastructure. If your work connects to AI's impact on workers, frame it as workers shaping the design and deployment of emerging workplace technologies. If you work in education, anchor it in learner-centered ecosystems with future-ready competencies — not traditional K-12 reform language.

Lead with proximate leadership credentials. Siegel has made community-proximate leadership an explicit strategic commitment. If your organization is led by people from the communities you serve, lead with this fact. It is a genuine differentiator with this funder — not a box to check.

Cultivate relationships with existing grantees. Siegel's network is the most reliable referral channel. Code.org, Transcend, Jobs for the Future, AFL-CIO Technology Institute, and Creative Commons are confirmed grantees who can provide introductions. Warm referrals carry disproportionate weight in a relationship-driven model.

Avoid the most common mistake: treating Siegel like a conventional grant funder with deadlines and submission portals. Organizations that understand and embrace the relationship-driven, thought-partnership model — and signal that understanding early — are far more likely to enter the pipeline than those who lead with a budget ask or formal proposal.