Technology./PHOTO ; AI
Artificial intelligence is transforming industries from medicine to finance. But in philanthropy, the sector meant to safeguard social progress, a digital divide is quietly widening.
A new report from Google.org and Fast Forward warns that while technology advances at record speed, most nonprofits remain years behind in adopting it.
The whitepaper, The Philanthropic Reset: How Philanthropy Can Lead in the Age of AI, released in September 2025, argues that the organizations addressing society’s toughest problems are falling behind precisely when they are needed most.
Without urgent digital investment, the report says, the social sector risks becoming “digitally fragile,” dependent on outdated systems and unable to leverage the power of AI to serve people effectively.
A Growing Gap Between Potential and Reality
AI now underpins everything from logistics to education, yet many nonprofits still operate without even basic digital tools.
The report describes a landscape where organizations are “asked to solve 21st-century problems with 20th-century tech.”
The authors say this is not because nonprofits lack creativity but because the rules of funding discourage innovation.
For decades, philanthropic grants have imposed strict limits on “overhead,” the share of money spent on technology, salaries, and long-term infrastructure.
Those restrictions, the paper argues, have left nonprofits “digitally immature.”
Nearly half report they do not spend enough on technology, and more than 80 percent of AI-driven nonprofits say they need additional funding to scale their work.
Maggie Johnson, vice president at Google.org and one of the report’s lead authors, said the sector faces an inflection point.
“There have been only a few times in my career when technology has opened possibilities that simply weren’t feasible before,” she said. “This is one of them.”
Technology Is No Longer Optional
The whitepaper frames AI not as a novelty but as a basic requirement “table-stakes infrastructure,” in the authors’ words.
Without it, the nonprofit sector cannot match the pace of social and environmental crises.
The report points to examples where technology has already transformed outcomes.
At John Jay College of Criminal Justice in New York, an AI-powered early-warning system built with DataKind and Google.org analyzed student data to flag those at risk of dropping out.
Advisors then intervened early. Within one year, senior graduation rates rose by 32 percent.
Another example, Tarjimly, used AI translation tools to connect refugees with interpreters.
The organization reached nearly 200,000 people, cutting translation response times in half. These results, the authors write, “are proof not of concept, but of impact.”
Shannon Farley, co-founder of Fast Forward, said the takeaway is clear.
“When nonprofits have the right tools and the right funding, they can move as fast and innovate as deeply as any startup,” she said.
Why Philanthropy Hasn’t Kept Up
The problem, the report argues, lies less in nonprofits themselves and more in the incentives created by philanthropy.
Funders typically reward short-term results the number of meals served or students reached, rather than long-term capacity building.
One-year grant cycles encourage “quick fixes over enduring tech builds.”
This mindset has created what researchers call a “starvation cycle”: funders demand efficiency and data but rarely pay for the systems that produce it.
The report urges philanthropists to break that cycle by treating technology as a core part of mission delivery, not a distraction from it.
Abhijit Banerjee, the Nobel-winning economist quoted in the report, offers a reminder that economic growth alone is insufficient.
“We need inclusive growth,” he said. Applied to philanthropy, the phrase takes on a new meaning: inclusion now depends on who has access to digital capacity.
The Uneven Geography of Innovation
The divide is not only financial but global. The authors warn that AI breakthroughs are “happening to the Global South, not with it.”
In many African countries, limited infrastructure and investment mean local innovators struggle to access advanced tools.
The result, they write, is “uneven accessibility at best.”
To illustrate what inclusion could look like, the paper highlights Karya, a social enterprise founded in rural India.
Its smartphone-based platform pays workers fair wages, often many times the local minimum, to create datasets used by partners such as Google and the Gates Foundation.
By 2030, Karya aims to expand to 20 countries and generate $1 billion in wages.
In Kenya, the agricultural nonprofit Digital Green used Karya’s technology to collect speech data in the Gikuyu language, improving an AI model for local farmers.
The localized system outperformed leading commercial models. The example, the report notes, shows that “community-generated data can drive smarter, more relevant AI.”
AI as Both Opportunity and Risk
Artificial intelligence could be a catalyst for equity or a new source of exclusion.
The report warns that automation is already reshaping labor markets, increasing demand for reskilling and safety-net services.
Without targeted investment, AI’s benefits may flow disproportionately to wealthier nations and sectors.
“AI will solve some problems but may exacerbate others,” the authors write.
They argue that philanthropic capital must help ensure “AI is making the change we want to see.”
That means funding not only tools but also governance, transparency, and ethics frameworks that keep technology aligned with public good.
James Manyika, Google’s senior vice president for research, said philanthropy can redirect attention away from profit-driven development.
“Most of the resources are focused on commercial applications,” he said. “We can change that.”
Bridging the Divide Through Collaboration
One recurring theme in the report is the need for partnerships that cross boundaries between sectors. Governments, nonprofits, startups, and academia each hold part of the solution, but rarely coordinate.
Examples of successful collaboration include Flood Hub, an AI forecasting system that Google.org and GiveDirectly used in Nigeria to deliver early cash aid to flood-prone communities.
Predictive data identified high-risk villages, triggering transfers to 7,500 people days before disaster struck. Families were able to evacuate safely and protect their livestock.
Another project, FireSat, combines AI modeling, satellite imagery, and open data to detect wildfires within minutes.
It brings together Google Research, the Earth Fire Alliance, Muon Space, and the Gordon and Betty Moore Foundation.
“By coordinating funding and science,” Johnson said, “we can help people and reduce damage.”
These partnerships, the report concludes, show that the most effective philanthropy is not about acting alone but about “building connective tissue” that links knowledge and infrastructure.
Closing the Knowledge Gap
If funders are to back more AI-powered initiatives, they must first understand them.
Yet a recent survey cited in the report found that only about one-third of grantmakers feel confident assessing the technical feasibility of AI proposals.
To fill that gap, initiatives such as Fund.AI a collaboration between Google.org, Fast Forward, and the Patrick J. McGovern Foundation offer hands-on training for donors.
Workshops teach participants how to evaluate ethical risks, interpret technical claims, and design grants that support innovation responsibly.
Kent Walker, Google’s president of global affairs, described the challenge simply:
“We can move from the ‘wow’ of AI to the ‘how,’ so that everyone benefits.”
The Stakes for Civil Society
Behind the statistics, the whitepaper paints a broader picture of urgency.
Public trust in institutions is low, global aid budgets are shrinking, and social problems are becoming more complex.
The authors argue that philanthropy’s survival as a credible force for good depends on its ability to adapt.
They urge funders to see technology not as a threat to human connection but as a tool to strengthen it.
With AI handling repetitive tasks from analyzing grant data to personalizing learning, nonprofits can redirect human effort toward empathy and relationship-building.
Demis Hassabis, co-founder of Google DeepMind, captured that hope:
“Some of the biggest problems facing us today, climate or disease, will be helped by AI solutions.”
The Path Forward
The report ends on a note of cautious optimism. Philanthropy, it argues, has the unique ability to take risks that markets and governments cannot.
By investing in digital capacity and shared infrastructure, funders can ensure that AI becomes a tool for inclusion rather than division.
The authors call this a “philanthropic reset,” a conscious decision to rethink priorities in the age of intelligent machines.
In practical terms, it means funding technology as infrastructure, collaboration as default, and learning as a permanent part of grantmaking.
If successful, that shift could transform not only how nonprofits work but what they can achieve. Predictive models might warn of famines before they occur.
AI tutors could narrow education gaps. Digital public goods could make entire systems more resilient.
The whitepaper closes with a reminder that progress is still a choice.
“The choices we make today,” it reads, “will shape the civic infrastructure of tomorrow.”
Credit:
This article is based entirely on The Philanthropic Reset: How Philanthropy Can Lead in the Age of AI (Google.org × Fast Forward, September 2025). All facts and quotations derive from that report.
