According to McKinsey’s latest survey, 78% of respondents from the private sector said their organisations use AI, up from 72% in early 2024 and 55% a year earlier. From algorithmic product recommendations to real-time fraud detection, AI is embedded into the daily operations of leading commercial corporations.
Yet, if you look at the social sector, including NGOs, nonprofits, and philanthropic foundations, the story is notably different. While over 70% of social innovators use AI in impact areas like healthcare, less than 1% of global corporate AI investment flows to these social applications.
Why is there quite a big gap? The truth is that philanthropy sits at a critical crossroads. It can either watch the AI revolution pass by or become the engine driving responsible, ethical, and sustainable AI for social good.
In this piece, I will explore why the social sector is behind, how philanthropy can help to smoothly integrate AI, and how philanthropists should harness this wave of innovation for real impact.
Why AI Leaves the Social Sector in the Dust
As we’ve understood, the social sector trails behind the commercial world in embracing AI technologies, and the reasons are both financial and structural. Nonprofits often work on tight budgets and face competing priorities. So, they can’t afford to allocate big sums of money on research and development, digital transformation, and rapid AI adoption compared to huge enterprises in finance or IT fields.
Beyond money, there is a severe shortage of technical expertise in social organisations. AI requires skilled data scientists, engineers, and strong technical support — a talent that seeks faster innovation cycles in the commercial tech industry. Obviously, without these capabilities in-house, nonprofits often struggle to identify relevant AI solutions, let alone their effective deployment or maintenance.
Then there’s the risk factor. Social sector organisations operate under a microscope, serving vulnerable social layers and handling sensitive data. There are some worries about potential ethical pitfalls: unintended harm, privacy violations, or biased algorithms. Still, these concerns are well-backed. Many AI systems inadvertently reinforce existing social inequalities if not carefully designed and tracked. So, it leads to slower experimentation and adoption.
AI can revolutionise social impact by enabling smarter resource allocation or efficiently predicting community needs. The question isn’t whether AI can — indeed, it can — but how philanthropy can break down barriers to turn responsible AI adoption into a reality in the social sector.
AI for Social Good — Seamless With Philanthropy
Let’s be honest: when we talk about “AI adoption,” we’re not just talking about money. It’s also about the ease of use, trusted partnerships, tailored tools, and removing friction. Philanthropy can be a game-changer in this case.
First, funders can help de-risk innovations. Many nonprofits hesitate to dive into AI as they don’t have enough time or margin for failed experiments. Philanthropic capital, especially if it’s long-term and flexible, gives organisations breathing room to test new tools, learn by doing, and adapt as they go. It’s a kind of safety net the social sector rarely gets.
Second, philanthropy can fund shared infrastructure, not just one-off projects. Think of open-source AI tools for nonprofits, sector-specific datasets, and direct access to training platforms. There are various initiatives which connect data scientists with social organisations to foster collaboration and use AI tools effectively. They show what’s possible when infrastructure is treated as a public good. To reach AI long-lasting impact, philanthropists must invest in foundational infrastructure to make access easier.
Capacity building is another major hurdle. The 2025 AI Benchmark Report by TechSoup and Tapp Network shows that while 85% of nonprofits are exploring AI tools, slightly more than 20% have a formal strategy in place. Even more telling — less than half of nonprofits rely on just one or two people to manage IT and AI decision-making. It’s a strategic vulnerability.
Philanthropy easily steps in to invest not only in tools but in people. From funding AI literacy workshops to backing the long-term talent pipeline, funders can help ensure social leaders understand and shape AI, not just react to it.
Riding the AI Wave Responsibly
Seamless adoption is necessary but not enough. Philanthropy also has to ensure that AI serves social good responsibly.
AI’s risks are well-known: bias, surveillance, hallucinations, and widening inequality. The social sector’s embrace of AI must come with a strong ethical framework to avoid harm. Philanthropists should deliver transparency, accountability, and inclusivity to AI projects by funding not just innovation but oversight and governance mechanisms.
Also, philanthropists have the real power to set the agenda. By giving priority to AI projects that align with equity and justice, funders can ensure the technology benefits marginalised communities rather than strengthening existing inequality.
This is definitely a moment of truth for philanthropy. The social sector mustn’t be a bystander while the AI revolution transforms society. I’m convinced that with deliberate action, philanthropists can help build an AI-powered future that is both innovative and fair. It will eventually turn AI from a privilege to the commercial sector into a social force for good.
For sure, the road ahead is complex and demands bold vision and responsible leadership, but the payoff is enormous: a smarter, more just, and inclusive world.
