10 Ways Small Charities Are Already Using AI
Practical examples of how UK charities are using AI right now — from transcription and grant writing to demand planning and donor reports.
AI in the charity sector is no longer theoretical. While headlines tend to focus on large institutions and experimental pilots, small charities across the UK are quietly using AI tools to solve practical, everyday problems. The Charity Digital Skills Report 2025 found that 76% of UK charities were actively using AI in their operations — and that figure is weighted heavily towards organisations with fewer than 25 staff. Small charities are not waiting for permission. They are getting on with it.
The reason is straightforward. Small charities face the same reporting, fundraising, and administrative demands as large ones, but with a fraction of the workforce. According to NCVO's UK Civil Society Almanac, the vast majority of charities in England and Wales are small organisations — 80% have an annual income below £100,000. These organisations cannot afford to hire grant writers, data analysts, or communications teams. AI tools give them access to capabilities that were previously out of reach — not by replacing staff, but by handling the repetitive work that consumes their time.
This article presents ten concrete ways small charities are already using AI in 2026. These are not futuristic possibilities. They are things happening right now, in community centres, advice offices, and project teams across the country. Where relevant, Plinth is referenced as an example because it was built specifically for the charity sector and bundles many of these capabilities into a single platform.
What you will learn:
- Ten specific, practical AI applications that small charities are using today
- How each use case works in practice, with realistic time savings
- Where to start if your charity has not yet adopted any AI tools
Who this is for:
- Charity managers and CEOs at organisations with fewer than 50 staff
- Frontline workers spending too much time on admin and reporting
- Trustees evaluating whether AI investment is worthwhile for their organisation
1. AI Transcription for Case Notes and Meeting Minutes
Frontline charity workers spend significant time writing up case notes after meetings, home visits, and support sessions. Research from the criminal justice voluntary sector highlights that frontline workers can spend a significant portion of their week on case recording. AI transcription tools can reduce that dramatically.
The process is simple. The worker records the session — with the beneficiary's consent — on their phone or laptop. AI transcription software converts the audio to text in minutes, often with speaker identification and automatic formatting. The worker then reviews, edits, and approves the notes rather than writing them from scratch.
Platforms such as Plinth integrate transcription directly into case management workflows. Rather than using a separate transcription tool and then copying text into your records, the audio is processed within the system, linked to the relevant beneficiary record, and formatted as a case note automatically. This removes an entire layer of copy-and-paste admin.
For meeting minutes, the same principle applies. Record the trustee meeting, the team planning session, or the partner call, and AI produces a structured summary with action items. According to the Charity Governance Code review 2025, better minute-taking is one of the simplest governance improvements small charities can make — and AI makes it practically effortless.
2. Photographing Paper Registers for Automatic Data Extraction
Paper sign-in sheets are still the default at hundreds of community programmes, youth clubs, food banks, and drop-in sessions across the UK. Staff know they need digital records for funders, but the manual process of typing up attendance data after every session is tedious and error-prone. Community organisations frequently report spending several hours per week on manual data entry from paper records.
AI-powered data extraction changes this entirely. A staff member or volunteer photographs the paper register using their phone. The image is uploaded to a platform like Plinth, and AI extracts names, dates, and any other information from the handwritten entries. The extracted data is matched against existing beneficiary records and added to the system automatically.
This is not a gimmick — it is one of the most immediately useful AI applications for grassroots charities. It works because the technology behind it (optical character recognition enhanced with modern AI models) has become remarkably good at reading handwriting. Even messy sign-in sheets with inconsistent formatting can be processed with high accuracy.
The time saving is substantial. What previously took 30 to 45 minutes of manual data entry per session now takes under two minutes, including the review step. For a charity running five sessions a week, that is over two hours reclaimed every week — time that goes straight back into service delivery.
The charities getting the most from AI are the ones applying it to their most routine, repetitive tasks — not the most complex ones.
3. Voice-Recording Conversations to Generate Case Studies
Every funder wants case studies. Every charity knows their work changes lives. But capturing those stories in a format that satisfies funders is one of the sector's most persistent pain points. Research consistently shows that small charities find producing case studies one of the most challenging aspects of funder reporting.
The barrier is not that charities lack compelling stories. It is that writing them up takes time, skill, and a particular kind of structured thinking that most frontline workers were not hired for. A caseworker might have a deeply moving conversation with a beneficiary, but turning that conversation into a funder-ready narrative with quotes, context, and outcome data requires an entirely different skill set.
AI solves this by removing the writing step. The worker records a five-to-ten minute conversation with the beneficiary — with informed consent — and the AI transcribes, structures, and formats it into a case study. Plinth's case study generator produces drafts that include a narrative arc, direct quotes, and links to relevant outcome data already in the system.
Staff then review and edit the draft, which typically takes 10 to 15 minutes rather than the 60 to 90 minutes a case study written from scratch would require. The output is not generic AI-generated text — it is built from the real words of real people, structured into a format funders recognise.
For charities that need to produce two or three case studies per quarter per funder, this represents a genuine step change in workload. It also means the stories themselves are richer, because they are captured in the moment rather than reconstructed from memory weeks later.
4. AI-Assisted Grant Writing from Actual Programme Data
Grant writing is one of the biggest time sinks in the charity sector. Grant applications typically take between 15 and 40 hours to complete, depending on the funder and grant size. For small charities submitting ten or more applications per year, that is a significant proportion of total staff capacity.
The problem is not just the time — it is the starting point. Most charities begin each application from a blank page, re-describing their organisation, their programmes, and their impact from memory. This leads to vague, aspirational language rather than the evidence-based claims that funders actually want to see.
AI grant writing tools change the process fundamentally. Rather than starting from nothing, Plinth's AI grant writer pulls actual outcome data, beneficiary numbers, case studies, and programme descriptions from your existing records and drafts application sections around them. The AI knows what your charity does because it has access to your data — not because a staff member spent hours describing it.
The result is a first draft that is already grounded in evidence. Staff edit and refine rather than create, and each application is automatically tailored to the specific funder's criteria. Early evidence from charities using AI-assisted grant writing suggests they can complete applications significantly faster than those writing manually, with no reduction in success rates.
| Grant Writing Approach | Average Time per Application | Evidence Quality | Consistency Across Applications |
|---|---|---|---|
| Manual (blank page) | 25–40 hours | Variable — depends on writer's memory | Low — tone and data change each time |
| Template-based | 15–25 hours | Moderate — relies on outdated templates | Moderate — templates go stale |
| AI-assisted from live data | 8–15 hours | High — pulls verified, current data | High — always uses latest records |
5. Automated Funder Reporting Tailored to Each Funder's Format
If grant writing is the first bottleneck, funder reporting is the second. A charity with six active grants might need to produce six different reports in six different formats on six different schedules. Charities consistently report spending excessive time adapting the same underlying data into different funder report formats.
The duplication is staggering. The data is the same — beneficiary numbers, outcomes achieved, activities delivered, budget spent. But each funder wants it presented differently. One wants a narrative report with case studies. Another wants a spreadsheet of outputs against targets. A third wants a two-page summary with a theory of change diagram.
Plinth's impact reporting tools address this directly. You maintain one central dataset of outcomes, activities, and evidence. When a report is due, AI generates a draft in the format that specific funder requires — pulling the relevant data, structuring it to match the funder's template, and tailoring the narrative emphasis to align with what that funder cares about.
A report that previously took a programme manager two full days to compile can be drafted in under an hour. The manager still reviews, edits, and approves every report — the AI handles the assembly, not the judgement. For small charities where the same person writes grants, manages programmes, and produces reports, this time saving can be the difference between sustainable operations and staff burnout.
Reporting burden is consistently identified by charity leaders as one of their top operational challenges. AI does not eliminate reporting — funders still need accountability — but it removes the mechanical repetition that makes it so draining.
6. Personalised Donor Impact Reports
Major donors increasingly expect to see what their specific contribution achieved. A philanthropist who gives £10,000 to a youth mentoring programme does not want a generic annual report — they want to know that their money funded 14 mentoring sessions, supported 8 young people, and contributed to a 35% improvement in school attendance among participants.
Until recently, producing this kind of personalised report was impractical for small charities. The data existed, but assembling it into a bespoke narrative for each donor was too time-consuming. Research consistently shows that major donors value personalised impact information and that it increases their likelihood of giving again — yet relatively few charities currently provide it.
AI closes this gap. Platforms like Plinth can generate individualised donor reports by linking donation records to programme outcomes. The AI drafts a narrative that describes what happened with that donor's specific contribution, pulling from real beneficiary data, outcome metrics, and case studies.
The reports are not fictional — they are mathematically allocated from actual programme data. If a donor funded 15% of a programme's annual budget, the report attributes 15% of the programme's outcomes to their contribution and illustrates that with specific examples. Staff review the draft, add personal touches, and send it.
For charities looking to improve donor retention and encourage repeat or increased giving, personalised impact reports are one of the highest-return activities available. AI makes them feasible even for organisations with small fundraising teams.
7. AI-Powered Service Directories
Many charities, particularly those in advice, signposting, or community anchor roles, maintain directories of local services. These directories — covering everything from housing support to mental health services to food banks — are essential for frontline staff making referrals. But keeping them accurate is a constant headache.
Services close, move, change their eligibility criteria, or adjust their opening hours. Local authority and charity-maintained service directories frequently contain out-of-date information because maintaining them manually is resource-intensive. Charity-maintained directories are particularly vulnerable because they have even fewer resources to keep information current.
AI-powered service directories address the maintenance problem. Instead of relying on staff to manually check and update every listing, AI can monitor changes (through web scraping, automated check-ins, and cross-referencing with other data sources) and flag entries that may need updating. Some systems can also process natural-language queries — a caseworker types "housing support for single mothers in Hackney" and the directory returns relevant, current results rather than requiring the worker to navigate rigid category structures.
Good signposting depends on good data. If a directory is six months out of date, it risks sending vulnerable people to services that may no longer exist.
For multi-service charities and community hubs, an accurate, searchable service directory directly improves the quality of support provided to beneficiaries. AI does not build the directory from scratch — it keeps an existing directory alive and useful.
8. Chatbots for Initial Beneficiary Triage and Signposting
Not every enquiry to a charity requires immediate human interaction. Many people contacting charities need basic information — "Am I eligible for this service?", "Where is the nearest session?", "How do I make a referral?" — that could be answered instantly rather than waiting for a staff member to respond during working hours.
AI chatbots are being used by a growing number of small charities to handle these initial interactions. A growing number of charities have implemented some form of automated chat or triage tool on their websites, with adoption increasing rapidly since 2023. The jump reflects both improved technology and growing confidence in the sector.
The most effective charity chatbots are not trying to replace human support. They are screening and routing. A chatbot on a domestic abuse charity's website might ask a series of initial questions and then route the person to the appropriate service — an immediate safety referral, a scheduled callback, or a self-help resource. A food bank chatbot might check eligibility, confirm session times, and explain what to bring.
| Interaction Type | Without Chatbot | With AI Chatbot |
|---|---|---|
| Basic eligibility check | Staff responds within 24–48 hours | Instant, 24/7 |
| Session time enquiry | Phone call during office hours | Instant, any time |
| Referral routing | Staff triages manually | Auto-routed by need |
| Complex support request | Staff handles directly | Chatbot escalates to staff |
| Out-of-hours contact | Voicemail or no response | Immediate signposting |
The key is appropriate boundaries. Chatbots should never attempt to provide therapeutic support or make safeguarding decisions. They should gather initial information, provide basic responses, and hand off to a human when the situation requires it. Done well, they mean that when a staff member does pick up the phone, they already have context and the person has already received immediate acknowledgement.
9. Predictive Analytics for Demand Planning
Small charities typically plan services based on gut feeling and last year's numbers. A food bank orders supplies based on what they used last quarter. A counselling service staffs sessions based on rough estimates of demand. This is understandable — these organisations rarely have the data infrastructure for anything more sophisticated. But it leads to waste, unmet demand, and reactive rather than proactive planning.
AI-driven predictive analytics is starting to change this, even for small organisations. By analysing patterns in existing data — attendance records, referral volumes, seasonal trends, local demographics — AI can forecast likely demand weeks or months ahead. Food banks and similar services using data-driven demand forecasting have reported meaningful reductions in both food waste and stock-outs.
For charities using platforms like Plinth that centralise attendance, case, and referral data, predictive analytics becomes a natural extension. The data is already there — it just needs to be analysed. AI can identify that referrals spike every January, that a particular session is consistently oversubscribed on Thursdays, or that a new housing development is likely to increase demand for family support services within six months.
This is not about complex data science. It is about pattern recognition applied to data that charities are already collecting. The Charity Commission's 2025 annual report noted that charities demonstrating data-informed planning scored higher on governance assessments — a practical incentive beyond the operational benefits.
Predictive analytics does require a foundation of reasonably clean, consistent data. Charities that have been recording attendance and outcomes digitally for six months or more typically have enough data for basic demand forecasting to be useful.
10. AI-Assisted Social Media Content and Fundraising Appeals
Content creation is a challenge for every small charity. You need social media posts, fundraising appeals, email newsletters, website updates, and event promotions — and you need them consistently. A 2024 survey by CharityComms found that 11% of small charities (those with 1-10 people) had no one with marcomms as part of their role, with content creation falling to whoever had capacity that week.
AI tools make content production faster and more consistent. Staff provide the raw material — an event date, a programme update, a beneficiary quote (with consent), a fundraising target — and AI drafts social media posts, email copy, or appeal text that can be reviewed and published in minutes rather than hours.
The most effective approach links content creation to actual programme data. Rather than writing a generic fundraising appeal, AI can generate a post that says "Last month, 47 young people attended our Saturday mentoring sessions. Each session costs £12 per person. Can you help us reach 60 this month?" — pulling the real numbers from the system rather than relying on approximations.
Plinth's data can feed directly into this kind of evidence-based content. When your outcomes, attendance, and impact data are centralised, generating compelling communications becomes a matter of asking the AI to turn data into narrative rather than inventing stories from scratch.
Research consistently shows that charities using data-driven, specific fundraising appeals see significantly higher average online donation values compared to those using generic messaging. The principle is simple: specific, verifiable claims are more compelling than vague ones, and AI makes it practical to produce them at scale.
How Do These 10 AI Use Cases Compare?
The table below summarises each use case by its implementation difficulty, typical time saving, and whether it requires specialist software or can be achieved with general-purpose AI tools.
| Use Case | Difficulty to Implement | Typical Weekly Time Saving | Requires Specialist Platform? |
|---|---|---|---|
| AI transcription | Low | 4–6 hours | No (but integration helps) |
| Paper register extraction | Low | 2–3 hours | Yes |
| Voice-to-case-study | Low | 3–5 hours | Yes |
| AI grant writing | Medium | 10–15 hours per application | Yes |
| Automated funder reporting | Medium | 8–12 hours per report cycle | Yes |
| Personalised donor reports | Medium | 3–4 hours per report | Yes |
| AI service directory | Medium | 2–3 hours | Yes |
| Beneficiary triage chatbot | Medium–High | 5–8 hours | Yes |
| Predictive demand planning | High | Variable (strategic value) | Yes |
| AI social media and appeals | Low | 3–5 hours | No (but data integration helps) |
Frequently Asked Questions
Do small charities really have the budget for AI tools?
Many AI tools relevant to charities are available on free or heavily discounted tiers. Plinth offers a free tier specifically designed for small organisations. General-purpose AI tools like transcription services often cost less than £20 per month. The key question is not whether you can afford AI — it is whether you can afford the staff time that AI would save. For most small charities, the arithmetic is strongly in favour of adoption.
Is AI safe to use with sensitive beneficiary data?
Data protection is a legitimate concern, and charities should not use consumer AI tools (like free chatbots) for sensitive data without understanding where that data goes. Purpose-built platforms like Plinth process data within controlled environments with appropriate security, encryption, and GDPR compliance. The ICO's 2025 guidance on AI in the charity sector recommends using sector-specific tools rather than general consumer AI for any work involving personal data.
Will AI replace charity workers?
No. Every use case in this article involves AI handling administrative tasks so that human workers can focus on relationships, support, and service delivery. The Charity Commission's 2025 annual report explicitly noted that AI in the sector is augmenting human capacity, not replacing it. The roles most affected are not frontline positions — they are the administrative burdens that prevent frontline workers from doing their actual jobs.
How much technical skill do staff need to use these tools?
Very little. The most successful AI implementations in small charities require no more technical skill than using a smartphone. Recording audio, taking photographs, reviewing and editing text — these are everyday tasks. The complexity is handled by the software, not the user. According to the Charity Digital Skills Report 2025, the main barrier to AI adoption is confidence, not competence.
Where should a charity start with AI?
Start with the task that consumes the most staff time relative to its value. For most charities, that is either data entry (use case 2: paper register extraction) or reporting (use case 5: automated funder reporting). These deliver the most obvious time savings and help build staff confidence before tackling more complex applications. See our guide to getting started with AI for charities for a step-by-step framework.
Can AI-generated content be used in formal grant applications?
Yes, provided it is reviewed and approved by a human before submission. AI drafts — staff decide. Funders care about the quality and accuracy of the application, not whether a first draft was generated by AI. The Association of Charitable Foundations confirmed in its 2025 guidance that AI-assisted applications are acceptable, provided the applicant organisation takes responsibility for all content submitted.
What about charities working with non-English-speaking beneficiaries?
Modern AI transcription and translation tools support dozens of languages, including those most commonly spoken by refugee and migrant communities in the UK. Plinth's transcription features can process conversations in multiple languages and produce English-language case notes. This is particularly valuable for advice services and refugee support organisations where language barriers add significant time to documentation.
How do we get trustee buy-in for AI adoption?
Present AI as a cost-saving and quality-improvement measure, not a technology project. Show trustees the specific time savings and their financial equivalent. A charity that saves 10 hours per week on admin at an average staff cost of £15 per hour is saving £7,800 per year — often more than the cost of the AI tools themselves. Our guide on AI strategy for charity trustees covers this in detail.
Recommended Next Pages
- AI for Charities: What Actually Works in 2026 — The comprehensive guide to AI adoption for UK charities
- AI-Powered Grant Applications — A deeper look at how AI transforms the grant writing process
- Digital Transformation for Charities — How to move from paper and spreadsheets to integrated digital systems
- Why Charities Struggle to Collect Impact Data — The root causes of poor impact data and how to fix them
- AI Strategy for Charity Trustees — What trustees need to know about AI governance and investment
Last updated: February 2026