Funders are growing increasingly interested in artificial intelligence (AI). Across the social sector, AI-powered solutions are being explored to improve learning outcomes, strengthen healthcare systems, support frontline workers, identify vulnerable populations, and make nonprofit operations more efficient.

But as more money moves towards AI, it raises an important question arises: Are funders paying only for technology, or are they funding everything it takes for that technology to create impact?

For most nonprofits, building an AI solution is only one part of the journey. The harder work often begins after the build: testing the tool with users, improving it based on feedback, strengthening the underlying data, training teams, changing workflows, generating evidence, and embedding the solution into government or institutional systems.

This is where many promising innovations stall. A short-term grant may be enough to build a prototype, but it is rarely enough to move from a promising tool to sustained adoption. For AI and digital transformation to create real impact, funders need to support the complete journey and not just the product.

Within this context, ‘patient capital’ becomes a condition for meaningful technological change. Patient capital broadly refers to funding that gives organisations the time, flexibility, and support to develop, adapt, and scale innovations. It does not mean lowering accountability; it means measuring the right things at the right time.

The disconnect between how AI innovation unfolds and how projects are typically funded emerges as a recurring theme in conversations with nonprofit leaders. Funding AI is not the same as buying technology. It involves financing the often long and uncertain process of organisational change.

Why AI Needs Patient Capital

A prevailing misconception about funding AI is that the project is complete once the technology has been built. The build is often the most visible part of the work, but it is rarely the hardest. Rekha Koita, Director and Co-founder of Koita Foundation, notes that successful digital innovation depends on user-centric design, repeated testing, organisational buy-in, and continuous adaptation based on what happens on the ground.

Read the full article about funding AI for lasting impact at India Development Review.