On April 16, 2025, FINCA, in partnership with London Business School, held its second meeting of a multipart series with international leaders in inclusive finance to address systemic challenges and develop innovative solutions to ending poverty.
Report Summary
AI systems today are largely shaped by a few dominant players controlling development and implementation. The result is energy-hungry systems that risk prioritizing scale over cultural relevance or environmental sustainability. To ensure AI serves the public good, it must be built and governed with the participation of the communities it aims to support. This includes incorporating culturally specific knowledge, designing LLMs with local languages, and establishing feedback loops that reflect real-world experiences, especially those of underserved populations.
As AI systems continue to expand, they also pose significant environmental challenges. The energy required to develop and run large-scale generative AI models is substantial, with some systems consuming as much power as entire nations. This environmental strain underscores the need for AI development to consider sustainability alongside innovation. Reducing AI’s carbon footprint through energy-efficient models, renewable energy sources, and responsible infrastructure planning must become a priority. In parallel, AI can also contribute to climate solutions, such as optimizing resource use, improving energy efficiency, and supporting environmental monitoring.
A new vision for AI centers on two key pillars: people and planet. To serve people, AI must advance inclusion, safeguard rights, and create meaningful value for underrepresented communities. To protect the planet, AI must integrate sustainable practices, responsible resource use, and climate resilience.
Realizing this vision requires collective effort across governments, companies, donors, and communities, grounded in the fundamental question: How can we make sure AI delivers solutions for the collective good?
