We used AI to ease staff burnout. Here’s what we learned.
A nonprofit built its own tool to unburden frontline staff — and the lessons reach well beyond AI.
By Erica Waterford
Contributor
September 10, 2026 | Read Time: 5 minutes
Most nonprofit organizations are slow to adopt new technologies. Few of us have resources to spare and there’s always a higher priority competing for attention, especially when it comes to direct-service providers.
Artificial intelligence is no exception. The whole sector is grappling with how and when to use AI to advance their missions, and the tools and capabilities change day by day. So when First Place for Youth — a national education, employment, and housing program for young people who are aging out of foster care or experiencing homelessness — had the chance to join an AI accelerator built for economic-mobility nonprofits, we jumped at it.
What we learned there is now helping us save staff time for the work that really matters.
Frame AI as extra capacity for your team.
Since First Place for Youth is, and has always been, a learning organization, we were open to AI from the beginning. Yes, we thought carefully about how it aligns with our goals and we wanted to have protections in place for the vulnerable youth we work with. But we were open to trying something new and accepting if it failed.
Before this year, we had been incorporating AI in small ways, such as showing young people how to use it in their job searches. Some staff, but not all, built up a bit of proficiency.
Our mindset toward AI is that it should never replace people, only add capacity. In fact, we’ve used predictive technology toward this end for over a decade through a program that tracks milestones in a young person’s life and predicts the next accomplishments that each step will enable them to achieve.
As an agency, we understood that technology has the potential to help move our mission forward. But we needed expert help to get smarter about AI and better at using it to address real operational challenges.
Target a problem that affects your whole staff.
Early this year, First Place for Youth joined 17 other economic-mobility nonprofits in the first cohort of the Economic Mobility AI Accelerator, a three-month program run by Jewish Vocational Service Bay Area, Arathi Ravier Consulting, Leading Educators, and Playlab. The program moved in three phases: understand how AI is reshaping the labor market; identify a priority problem inside your own organization; then build and test a custom tool against a real workflow. Each organization worked with a dedicated coach to narrow the problem and plan the pilot.
First Place for Youth selected two people — one direct-service staff member and one from the leadership team — to ensure both on-the-ground insights and broader organizational perspectives. When it came time to pilot a tool, we decided to address a problem that affects most of our staff (78 percent of whom work in direct service): burnout from juggling time-consuming administrative tasks on top of their busy caseloads.
To address this, we designed an AI tool we called “Note Ninja” into which staff can talk or type what occurred during their meeting with a young person and receive a streamlined summary, formatted in a case-management framework, that identifies key focus areas and next steps to take into the following meeting.
Our initial pilot was with a small group of eight staff for three weeks. During the first week, participants were asked to use the tool for all their meetings. In week 2, using the tool was voluntary, but all eight participants opted to continue doing so — an indication that what we created was both easy to adopt and already producing value for staff.
By the third week, staff members outside the pilot group were asking if they could also get access to Note Ninja.
Keep the tool simple so staff want to use it.
In pre- and post-surveys of the Note Ninja pilot, we found that:
● 100 percent of users reported a decrease in administrative burden
● 100 percent reported reduced burnout
● 80 percent said it gave them more time to work with young people
● 80 percent reported they were no longer working overtime
Prior to the pilot, we anticipated there would be some pushback, technology learning difficulties, or utilization concerns. Surprisingly, we got no pushback from staff about using the tool, despite intentionally selecting some individuals who we thought would be more resistant to adopting it. The tool we created was purposely simple and we made sure that staff had clear step-by-step instructions on how to use it.
Our next phase will surface additional lessons in preparation for full agency integration. That includes continuing to address challenges we found in the testing process, such as ensuring data privacy and scaling in a cost-efficient manner.
What we’d tell another nonprofit starting out.
Regardless of your organizational size or the frontline staff you have, any nonprofit can apply our lessons to reduce busywork, build capacity, and increase staff buy-in on AI.
- Be open to learning and to failure. Wanting to prove something works versus wanting to learn whether it works are two different postures. The first can get in the way of implementing something like AI, because you have to be OK with things not working and genuinely want to understand how to do better. That’s why we built our pilot the way we did: a real test period, a survey before and after, and a second week where using the tool was entirely optional. If staff had walked away in week 2, we’d have had our answer. They didn’t, but a learning mindset meant we were prepared for either outcome.
- Create or find spaces to get hands-on. The Economic Mobility AI Accelerator gave us access to experts, including platform pros who could answer questions about the tools themselves and strategy specialists who could talk about the possibilities and limitations of integrating AI. We also had the chance to learn directly from our peers; seeing other organizations addressing similar problems and running into their own barriers informed how we built and piloted our tool. Seek out training and experts who can provide similar technical assistance.
- Funders should actively support capacity building and experimentation. Learning opportunities and access to tools cost money. At First Place for Youth, a lot of our ability to adopt AI was thanks to a tech grant that gave us free access to Claude, and we were able to participate in the accelerator itself because a funder sponsored our participation. Donors rightfully want to see results from their grantees, and we know firsthand that AI can free up capacity to make more of a difference in the lives of the people we serve. That’s definitely something worth funding.
