What tech funders like OpenAI need to do differently
In Part 1, I argued that speed without strategy undermines the very legitimacy tech companies seek through philanthropy. So what does strategic AI philanthropy actually look like?
As regulators globally scrutinize AI’s social impact, these principles offer a pathway to genuine community partnership rather than performative compliance.
Below, I outline five interconnected principles for building bridges—not just shields—between AI innovation and community priorities. Each principle reinforces the others, creating a framework that moves beyond defensive giving toward genuine partnership.
1. Fund Capacity, Not Just Projects
Too often, grants are restricted to specific pilots or short-term programs. While these can spark innovation, they rarely build lasting strength. Communities don’t just need experiments; they need stability. That means funding operating budgets, staff development, and organizational infrastructure. [EXAMPLE NEEDED: Instance where unrestricted funding enabled an organization to respond effectively to AI-related challenges]
A well-placed unrestricted grant can do more to build resilience than a large but narrow project grant. The most effective philanthropy supports the foundation that makes impact possible—and that foundation becomes the platform for everything else: responsive programming, community-defined metrics, and sustained partnership.
2. Build Equity In From the Start
Equity can’t be an afterthought. It has to be baked into the design of funding strategies. That means intentionally supporting BIPOC-led organizations, grassroots groups, and frontline practitioners who are closest to the challenges AI may accelerate—job displacement, misinformation, and inequitable access to tools. These organizations often have less access to large institutional funding, yet their proximity to community makes them essential partners.
Equity isn’t just about who receives funds; it’s about who has decision-making power. This means reserved seats on advisory committees, dedicated percentages of funds directed to grassroots organizations, and funding structures that don’t require nonprofits to compete against better-resourced institutions for the same dollars.
3. Redefine Speed
Yes, philanthropy should move faster. But speed needs to be redefined. Fast grants are useful for early response or pilot efforts, but they should be paired with longer-term commitments. Communities can’t rely on one-year experiments that vanish when the funding ends. A balanced model—quick initial support, followed by multi-year investments—creates both responsiveness and durability.
This dual-track approach requires funders to think differently about risk. Instead of minimizing risk through short-term grants, they accept the risk of longer commitments in exchange for deeper impact. Urgency and patience can, and must, coexist.
4. Measure What Matters to Communities
Tech companies often measure success through product metrics: scale, growth, rapid adoption. But community impact operates on different indicators and timelines. Trust built over years, people trained for sustainable employment, organizations strengthened to serve more effectively—these outcomes don’t fit neatly into quarterly reports.
Funders need dual accountability: to shareholders expecting measurable returns AND to communities defining impact on their own terms. This means developing metrics collaboratively, accepting qualitative alongside quantitative measures, and understanding that some of the most important outcomes—like community trust or organizational resilience—emerge slowly and resist easy quantification. Otherwise, the metrics risk distorting the work itself.
5. Co-Design With, Not For, Communities
One of the simplest but most often overlooked shifts is to bring practitioners and community leaders directly into decision-making. Too much philanthropy is designed in boardrooms, not in the places where change is happening. This represents a fundamental shift in power: from corporations determining how to help communities, to communities determining how corporations can best support existing priorities.
Co-designing programs with communities ensures that funding meets real needs, not imagined ones. It also strengthens legitimacy: when people see their priorities reflected, they are more willing to engage and collaborate. [EXAMPLE NEEDED: Instance of successful co-design process from your experience]
Moving From Shield to Bridge
In her piece, Gayle Roberts described philanthropy as a “shield” that helps companies like OpenAI protect themselves from criticism and regulatory pressure. But philanthropy can’t just be a shield—it has to be a bridge. A bridge between innovation and justice, between global technology and local communities, between speed and sustainability.
Each principle above represents a different span of that bridge: capacity funding creates stable foundations, equity work ensures the bridge reaches the right communities, redefined speed balances urgency with sustainability, community-defined metrics ensure the bridge serves its intended purpose, and co-design ensures communities help determine where the bridge should go.
For OpenAI and other funders in the AI space, the opportunity is clear: invest ambitiously, but wisely. Write big checks, but also write flexible ones. Move fast, but in partnership with those who move differently. Start with pilot programs that test these principles before scaling them—demonstrating that bridge-building approaches deliver the legitimacy and community support that defensive strategies cannot.
Above all, understand that legitimacy comes not from the size of a gift, but from how deeply it reflects community priorities.
If AI is to transform the future, philanthropy must transform with it—rooted not just in speed, but in equity, trust, and shared purpose.
What tech funders like OpenAI need to do differently
In Part 1, I argued that speed without strategy undermines the very legitimacy tech companies seek through philanthropy. So what does strategic AI philanthropy actually look like?
As regulators globally scrutinize AI’s social impact, these principles offer a pathway to genuine community partnership rather than performative compliance.
Below, I outline five interconnected principles for building bridges—not just shields—between AI innovation and community priorities. Each principle reinforces the others, creating a framework that moves beyond defensive giving toward genuine partnership.
1. Fund Capacity, Not Just Projects
Too often, grants are restricted to specific pilots or short-term programs. While these can spark innovation, they rarely build lasting strength. Communities don’t just need experiments; they need stability. That means funding operating budgets, staff development, and organizational infrastructure. [EXAMPLE NEEDED: Instance where unrestricted funding enabled an organization to respond effectively to AI-related challenges]
A well-placed unrestricted grant can do more to build resilience than a large but narrow project grant. The most effective philanthropy supports the foundation that makes impact possible—and that foundation becomes the platform for everything else: responsive programming, community-defined metrics, and sustained partnership.
2. Build Equity In From the Start
Equity can’t be an afterthought. It has to be baked into the design of funding strategies. That means intentionally supporting BIPOC-led organizations, grassroots groups, and frontline practitioners who are closest to the challenges AI may accelerate—job displacement, misinformation, and inequitable access to tools. These organizations often have less access to large institutional funding, yet their proximity to community makes them essential partners.
Equity isn’t just about who receives funds; it’s about who has decision-making power. This means reserved seats on advisory committees, dedicated percentages of funds directed to grassroots organizations, and funding structures that don’t require nonprofits to compete against better-resourced institutions for the same dollars.
3. Redefine Speed
Yes, philanthropy should move faster. But speed needs to be redefined. Fast grants are useful for early response or pilot efforts, but they should be paired with longer-term commitments. Communities can’t rely on one-year experiments that vanish when the funding ends. A balanced model—quick initial support, followed by multi-year investments—creates both responsiveness and durability.
This dual-track approach requires funders to think differently about risk. Instead of minimizing risk through short-term grants, they accept the risk of longer commitments in exchange for deeper impact. Urgency and patience can, and must, coexist.
4. Measure What Matters to Communities
Tech companies often measure success through product metrics: scale, growth, rapid adoption. But community impact operates on different indicators and timelines. Trust built over years, people trained for sustainable employment, organizations strengthened to serve more effectively—these outcomes don’t fit neatly into quarterly reports.
Funders need dual accountability: to shareholders expecting measurable returns AND to communities defining impact on their own terms. This means developing metrics collaboratively, accepting qualitative alongside quantitative measures, and understanding that some of the most important outcomes—like community trust or organizational resilience—emerge slowly and resist easy quantification. Otherwise, the metrics risk distorting the work itself.
5. Co-Design With, Not For, Communities
One of the simplest but most often overlooked shifts is to bring practitioners and community leaders directly into decision-making. Too much philanthropy is designed in boardrooms, not in the places where change is happening. This represents a fundamental shift in power: from corporations determining how to help communities, to communities determining how corporations can best support existing priorities.
Co-designing programs with communities ensures that funding meets real needs, not imagined ones. It also strengthens legitimacy: when people see their priorities reflected, they are more willing to engage and collaborate. [EXAMPLE NEEDED: Instance of successful co-design process from your experience]
Moving From Shield to Bridge
In her piece, Gayle Roberts described philanthropy as a “shield” that helps companies like OpenAI protect themselves from criticism and regulatory pressure. But philanthropy can’t just be a shield—it has to be a bridge. A bridge between innovation and justice, between global technology and local communities, between speed and sustainability.
Each principle above represents a different span of that bridge: capacity funding creates stable foundations, equity work ensures the bridge reaches the right communities, redefined speed balances urgency with sustainability, community-defined metrics ensure the bridge serves its intended purpose, and co-design ensures communities help determine where the bridge should go.
For OpenAI and other funders in the AI space, the opportunity is clear: invest ambitiously, but wisely. Write big checks, but also write flexible ones. Move fast, but in partnership with those who move differently. Start with pilot programs that test these principles before scaling them—demonstrating that bridge-building approaches deliver the legitimacy and community support that defensive strategies cannot.
Above all, understand that legitimacy comes not from the size of a gift, but from how deeply it reflects community priorities.
If AI is to transform the future, philanthropy must transform with it—rooted not just in speed, but in equity, trust, and shared purpose.