For “CXO AI Playbook,” Business Insider takes a look at mini case studies about AI adoption across industries, company sizes, and technology DNA. We’ve asked each of the featured companies to tell us about the problems they’re trying to solve with AI, who’s making these decisions internally, and their vision for using AI in the future.
Founded in 1979, Mercy Corps is a global humanitarian aid organization based in Portland, Oregon. It operates in more than 40 countries, and has roughly 4,000 employees supporting communities affected by poverty, disaster, conflict, and the climate crisis. The majority of its staff members are from the countries where they work.
Situation analysis: What problem was the organization trying to solve?
In the developing world, agricultural crises like droughts, crop failures, and loss of livestock can rapidly escalate into humanitarian crises. Mercy Corps has experience anticipating these emergencies and reducing their impact. But a lack of timely, reliable data often prevents that knowledge from reaching the right people at the right time.
Alicia Morrison, the director of data science at Mercy Corps, saw potential in generative AI for getting relevant information into the hands of decision-makers more quickly.
The goal was to build a tool that could provide aid workers with quick, reliable answers to the day-to-day questions they face in the field. The answers would be based on past projects, research, and proven approaches, and include links to sources and citations so workers can know where the information comes from.
“Making that tool available to the people doing the work helps them learn from what’s been done and imagine new possibilities,” she told Business Insider. “That’s when we get the most creative ideas and uses of information.”
Key staff and partners
Mercy Corps took part in Tech To the Rescue’s AI for Changemakers program, a global accelerator that helps nonprofits experiment with AI. Through intensive, short-term training programs, Tech To the Rescue gives organizations a chance to pitch AI ideas and connect with private sector partners who can help bring them to life.
Mercy Corps matched with Cloudera, a software company focused on data management, analytics, and AI. “They had the idea and we believed we could contribute our time, resources, and skills and add value,” said Rob Dickens, a solutions architect at Cloudera.
Cloudera donated engineering time and platform credits to develop the product, which is called the AI Methods Matcher. Dickens said development took about seven weeks, and the tool runs on Cloudera’s AI Inference service, which uses Nvidia technology.
AI in action
Methods Matcher uses a type of generative AI called retrieval-augmented generation. It draws on an archive of successful projects to search for relevant information, summarize it, and offer recommendations. Now, decisions that aid workers make on the ground — from calculating vegetation health to tracking fertilizer distribution — can be guided by data.
Morrison said the tool speeds up decision-making by reducing the time and manual research required to analyze large volumes of information. With Methods Matcher, Mercy Corps’ teams can identify actions that have worked elsewhere and get evidence-based suggestions in real time.
For example, in countries facing severe inflation, Mercy Corps often provides multipurpose cash assistance. But the organization needs to know the purchasing power of that cash to make an impact. In this case, an aid worker in the field might ask the tool, “How do I determine how much cash aid to give people in a region with rising inflation?”
Methods Matcher responds with a tailored answer based on past Mercy Corps projects and research. Aid workers can ask follow-up questions in the same session, and because the tool “remembers” the conversation history, they can build on earlier questions without having to start over.
The tool helps teams in the field quickly access information without waiting for support from HQ. “They can see for themselves how valuable this kind of information can be,” Morrison said.
Did it work, and how did leaders know?
Since the tool’s launch in November 2024, Morrison said that while they have yet to report metrics on the tool’s impact, there has been strong early adoption among field teams. Mercy Corps is now working with Cloudera to expand Methods Matcher, develop new AI tools, and build data literacy across the organization.
It’s also gathering feedback on Methods Matcher from staff to understand what’s working and what needs improvement.
“We’re a nonprofit, so we don’t have a big team of in-house AI experts,” Morrison said. “We’re learning as we go — figuring out how to maintain these tools, how to evaluate them, and how to get people across the organization on board for the long haul.”
What’s next?
Mercy Corps has experienced a significant shift in funding in recent months, but Morrison said Methods Matcher and other AI tools remain “a priority investment area.” She added that the organization will continue to improve based on team feedback.
Dickens said Cloudera plans to bring agentic AI into the tool through its Agent Studio, automating tasks like gathering real-time data, analyzing trends, and generating reports or recommendations. This will allow Methods Matcher to surface relevant news and social media reports from affected areas, making it more responsive to events on the ground.
“Aid workers will get richer, real-time context instead of manually compiling daily or monthly reports,” he said.
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