Over the summer I had the privilege of facilitating the Charity AI Leadership Accelerator programme in collaboration with Microsoft, where we trained over 100 leaders from small and large charities. One of the most inspiring parts of the programme was hearing directly from smaller organisations about how they’re already using AI to tackle everyday challenges.
When I think about these conversations, what strikes me is how grounded they were. While much of the discussion around AI in our sector focuses on future possibilities or fears about job displacement, these charities are getting on with solving problems that were making their teams’ lives harder. It’s exciting to see small charities and non profits innovating and unlocking the benefits of these technologies.
Here are 3 case studies of small charities and non profits who have benefited from AI which we shared with delegates on the programme.
Climate Barometer’s database challenge
Climate Barometer faced something that will be painfully familiar to many small charities – multiple contact spreadsheets scattered everywhere with no way to track interactions or see the full picture of their relationships. Media contacts here, partners there, general contacts somewhere else entirely. It’s the kind of messy reality that happens when you’re focused on delivering your mission and you don’t have time to sort out your systems- and let’s face it, we have all been there.
Climate Barometer turned to ChatGPT Plus. They used it to analyse their existing spreadsheets and suggest a better data structure, then asked ChatGPT to write prompts for Airtable AI to automatically create database tables. They even had ChatGPT draft user guides for their team, who were new to Airtable.
The results were really positive. They saved half a day on data structure work and three hours on database development. More importantly, they now have a linked database connecting all their contact information and interactions. While they’re still testing and adopting new ways of working, early benefits include faster reporting to funders. As their data grows, they’ll be able to analyse which press releases actually get media coverage.
Oswin Project tackles VAT receipts
When Oswin Project registered for VAT, they faced a task that would make anyone’s heart sink – sorting through more than 1000 invoice PDFs to work out how much VAT they’d paid on each. For a small charity, this represented at least a week of someone’s time that could have been spent on their actual work.
They used Claude to write a small Python programme that sorted through their folder of invoices automatically. The programme organised invoices into folders based on date and created a spreadsheet showing invoice name, total amount, and VAT amount. As they put it, “Took him a few goes to get it right but then it nailed it!”
What I found particularly interesting was how they described AI approaching the problem differently each attempt. It’s a reminder that working with AI isn’t always straightforward, but persistence pays off. Iterating in partnership with the tools can lead to better results. They avoided at least a week of manual work and processed over 1000 documents automatically with much less risk of human error.
Children’s University makes data meaningful
This case study is based on a brilliant LinkedIn post by Chris Rhodes of The Tech Dept. Children’s University had another classic small charity challenge- some great data and insight which they knew they could do more with, if they could access the right tools and support. Their learning log showed raw numbers of extracurricular hours across categories, but it wasn’t engaging for the children using it. Staff were spending valuable time reading and interpreting data to help pupils understand their own progress.
Their solution sends existing data securely to an LLM for summarisation. The AI creates an engaging narrative for children about their progress instead of just showing numbers. The response comes back in a structured format within their learning log template, with the AI acting as a ‘virtual mentor’ explaining the data to pupils.
Staff no longer need to spend time interpreting data for pupils, and children get a personalised narrative about their achievements. As one teacher said, “Great as it was set to save so much staff time.” The future potential includes AI recommending specific activities for more rounded portfolios.
What this means for our sector
What I love about these examples is the incredible problem solving, creativity and innovation being modelled by small charities who are leading the way with AI- qualities which charities of all sizes can learn from.
These organisations didn’t need huge budgets or technical teams. They were laser focused on what wasn’t working, they were willing to experiment, and they had the confidence to figure things out and do things differently. What I love about these examples is how they are helping charities to spend more time on mission critical work, supporting the communities they serve.
The bigger question these case studies raise is about how we build capacity in our sector. If small charities can solve complex problems with readily available AI tools, what does that mean for how we think about resources, skills, and support? How do we ensure that all charities regardless of size or technical confidence, can benefit from these developments? And are we doing enough to celebrate the stories of small charities who are innovating with AI?
If you’re a small charity who is doing something exciting with AI we’d love to platform your work on our blog. Please email me on zoe@zoeamar.com.
PS If you’re a small charity leader looking to develop your next steps in AI please take a look at the free video resources we created in collaboration with Microsoft.