The AI impact flywheel: How inclusive AI can catalyze transformative growth

We live in extraordinary times, characterized by exacerbating global challenges and exponential AI advances. With over $1.5 trillion already invested, the AI revolution continues to accelerate. Yet, less than 1% of this investment is directed towards social impact and most benefits are confined to high-income economies. As AI capital, data and compute become increasingly controlled by a small number of firms and countries, they shape how systems are built and which problems are prioritized. Without intentional design and equitable distribution, this AI era risks amplifying inequality, concentrating power and reinforcing systemic bias.

To put the AI boom in perspective, total global AI investment is approaching a scale unmatched by previous comparative innovation waves, with capital deployed in 2025 alone estimated to have eclipsed the inflation-adjusted costs of the atomic bomb and moon landing programmes combined. At the same time, some 239 million people worldwide require urgent humanitarian assistance, while legacy systems struggle to fund even half of the most prioritized needs. A third of humanity remains offline and more than 250 million children are without access to education. Most AI systems are trained on just 100 of the world’s more than 7,000 languages, reinforcing the concentration of transformative technologies in a handful of advanced economies. This divergence signals not a failure of innovation, but of alignment. A new operating model is urgently needed.

To deliver better outcomes across sectors and advance AI for shared value, governments, businesses and civil society must act in alignment. Strategic philanthropy can serve as the catalytic partner at this intersection, absorbing early-stage uncertainty and carrying promising solutions from proof to practice. When aligned, these actors form a flywheel: public policy sets direction, philanthropy de-risks experimentation, business scales solutions and success reinforces confidence across the system.

Focusing AI deployment on inclusive development and practical applications can convert concentrated acceleration into widespread systemic growth. With 85% of the world’s population living in the Global South and two-thirds under the age of 35, redirecting even a small fraction of global AI investment towards social innovation could deliver trillions in economic potential and catalyze grassroots ingenuity for generations. A people-first approach need not constrain AI’s ambition; it may prove its most enduring expression, harnessing innovation to address humanity’s most urgent and systemic challenges.

Many frontier markets have embraced mobile technology, fintech and blended finance to leapfrog outdated models. AI must now follow a similar path. Achieving this requires connected capital, open-data ecosystems and cross-sector partnerships that democratize access and accelerate equitable impact. This is where philanthropy can become incredibly useful, supporting the foundations that markets alone struggle to sustain and establishing investment frameworks that crowd in diverse sources of finance. Ultimately, the next great leap forward will not be defined by how smart our systems become, but by how inclusive, fair and empowering we make them.

AI is increasingly being applied in novel ways to solve real-world problems. AI-powered early warning systems, for example, now flag health and climate risks in vulnerable communities before they turn catastrophic, facilitating new insurance and adaptation mechanisms that, in turn, enable additional financing and innovation. From smarter diagnostics and logistics to hyper-local commerce and education, initial deployments are demonstrating how the next wave of AI can deliver practical and scalable benefits across developing regions.

Uniting public, private and philanthropic resources can help institutionalize these programmes, creating ecosystems that serve as blueprints for others. The UAE’s own development model is an example and an invitation, shaped by rapid experimentation, course correction and the recognition that scaling inclusive AI requires continual investment in skills, governance and public trust. As an early mover, the UAE launched its national AI strategy nearly a decade ago, appointed the world’s first Minister of State for AI and opened the world’s first AI-dedicated university. National AI strategies, supportive policies and a growing network of private and philanthropic institutions have helped cultivate fertile ground for AI-driven social applications addressing local and shared challenges.

Many of these use cases, whether supply-chain optimization, agricultural innovation or wildlife conservation, can be adapted and scaled globally. As a rising hub for AI and strategic philanthropy, the UAE's combination of convening power and execution capability helps advance inclusive solutions, ensuring social initiatives compete for capital alongside commercial ones.

Amid AI’s multi-trillion-dollar infrastructure boom, with its focus on sovereign control of critical AI capacity, there is an urgent opportunity to make AI a tool for global convergence, not divergence. Actionable frameworks for technology transfer, capacity-building and governance can enable fast-growing tech hubs to share open-source tools with late-start economies, allowing them to leapfrog legacy systems, capture productivity gains and unlock competitive advantages. Pooled finance, open data and public–private collaboration can strengthen regional connectivity, while localized AI applications create new links in global value chains and reduce barriers to cross-border investment.

AI-for-good initiatives have shown immense potential, but wider adoption and public trust depend on the right incentives and enabling systems. Clear guardrails are essential to mitigate risk, uphold data sovereignty and ensure equitable access. Encouraging data sharing is also key: demonstrating how AI can translate fragmented data into actionable, hyper-local insights builds confidence and investment readiness. In turn, AI-driven insights can strengthen the case for investment and incentivize sustainable behaviour change, driving further demand for digital capabilities and broader inclusion.

As traditional aid structures falter, we must rethink how resources are mobilized for impact. By applying AI to build scalable solutions across education, healthcare, infrastructure and livelihoods, we can shift from reactive relief to proactive empowerment. Integrating financial and non-financial resources will accelerate adoption and generate economic and social value. AI can also streamline philanthropy by improving targeting, measurement and efficiency, while cross-sector collaboration can expand AI literacy and grow engineering talent in emerging economies – broadening access to diagnostics, localizing language tools and catalyzing entrepreneurship.

In these extraordinary times, progress must be measured not by speed alone, but by who benefits. Making AI more inclusive requires developing systems and solutions: investing in skills, research and talent, while simultaneously scaling real-world applications. It means empowering communities of practice – from teachers and farmers to medics and merchants – to apply AI to shared challenges. The imperative is to align AI with social innovation and ensure technological acceleration delivers inclusive, transformative outcomes.