As a Business Intelligence expert passionate about creating compelling visual stories from big data, Chloe Maraina has a unique perspective on the intersection of data science, AI, and social impact. With a deep understanding of data management and integration, she helps organizations unlock the narratives hidden within their numbers. In our conversation, we explored how agentic AI is moving beyond a theoretical concept to become a practical, mission-critical tool for resource-constrained nonprofits. Chloe explained how organizations are navigating the initial challenges of implementation, transforming routine data-pulls into powerful storytelling, and leveraging agent-assist tools to enhance the human element of their work. We also looked ahead to how this technology will reshape the experience for donors and volunteers, fundamentally changing the operational landscape of the third sector.
Lori Freeman described a common nonprofit challenge as a “valley of despair” stemming from undocumented processes. How are tools like Agentforce Nonprofit helping organizations climb out of that valley, and what’s a tangible first step a nonprofit can take to find a process ripe for AI automation?
That “valley of despair” is a feeling I’ve seen firsthand, and it’s incredibly frustrating for mission-driven teams. It’s that sinking feeling of knowing you have valuable data, but it’s scattered and the processes to use it are locked in people’s heads. Agentforce helps by providing a framework to start mapping those processes. The most practical first step for any nonprofit isn’t to look for the most complex problem to solve, but the most repetitive one. Think about the tasks that make your staff sigh. Is it compiling metrics for grant reports every month? Is it manually sorting through applications? That’s your starting point. America On Tech did this brilliantly. They saw their single data manager was spending days fulfilling unique reporting requests and realized that was a perfect, high-impact task for an agent. Start there, with a known pain point, and build momentum.
You mentioned America On Tech, which impressively cut its data request time from three days to just one hour. Could you elaborate on what it means to move from “data crunching to data storytelling” and paint a picture of a specific narrative they can now create?
Absolutely, because that metric is just the beginning of the story. Before, the three-day crunch was a purely reactive process—a frantic scramble to pull numbers to meet a deadline. There was no time for analysis or insight. Now, in that one hour, they can go so much deeper. Instead of just giving a funder a spreadsheet, they can build a compelling narrative. For instance, they can now instantly generate a report that shows not just the number of students served in their Los Angeles program, but also a chart visualizing their progress through different tech career pathways. They could overlay that with hyperlocal data, showing how their work directly impacts a specific community a funder cares about. It transforms the conversation from “Here are the numbers you asked for” to “Here is the profound, measurable impact your investment is having on young lives, and here’s a visualization of that journey.”
The Participant Management tool sounds like a powerful ally for case managers. Can you walk us through what a typical client interaction looks like with this AI agent assisting in the background?
Imagine a case manager on a call with a client who needs support. In the past, the case manager would be frantically trying to take notes while simultaneously searching their CRM for the client’s history. With the Participant Management agent, that cognitive load is lifted. As the conversation happens, the agent can surface critical information in real-time, like a note saying, “This participant was referred by a partner agency, flag for a follow-up.” It might also prompt the case manager with relevant recommendations based on the conversation flow and the client’s CRM data. Then, at the end of the call, instead of the case manager blocking off 15 minutes to type up detailed notes, the agent will present a concise summary for their review. This allows the case manager to remain fully present and empathetic during the call, focusing on the human connection rather than the administrative burden.
Looking at the tools on the horizon, like Donor Support and Volunteer Capacity, how do you see them transforming the day-to-day experience for a nonprofit’s crucial supporters? Could you share a scenario where one of these agents creates a win-win situation?
These upcoming agents are all about improving the experience for the people who fuel the organization’s mission. Let’s take the Volunteer Capacity agent. A potential volunteer might visit the nonprofit’s website on a weekend, feeling inspired to help. Traditionally, they’d fill out a form and wait days for a response from an overworked coordinator. With the agent, they could have an immediate, interactive experience. The agent could ask about their skills, match them to an urgent need—like designing a flyer for an event—and even get them provisionally signed up right then and there. The volunteer feels valued and immediately engaged, and the nonprofit fills a critical skills gap without delay. It’s a perfect example of how automation can foster a stronger, more responsive human community around a cause.
What is your forecast for the adoption of agentic AI within the nonprofit sector over the next five years?
Given the incredibly challenging funding landscape, where giving patterns have remained largely flat for decades while demand for services soars, I believe agentic AI will move from being an innovation to an absolute necessity. Over the next five years, we’ll see a dramatic acceleration in adoption. It will start with automating back-office tasks like grant reporting, as America On Tech has done, but it will quickly expand to front-facing interactions. I forecast that these tools will become as standard as a CRM system is today. The conversation will shift from “Should we use AI?” to “How can we strategically deploy AI to free up our people to do what they do best: build relationships, deliver services, and advance the mission?” It will be the key for survival and scale for so many vital organizations.
