As “92% of nonprofits are using AI, but only 7% are using it strategically” (Virtuous, 2026 Nonprofit AI Adoption Report), that gap is where the opportunity lies.
For nonprofits, where time, funding, and capacity are always stretched, generative AI offers something powerful: the ability to do more with less, without burning out your team.
What is Generative AI (in Plain English)
Generative AI refers to tools that can create content, such as text, images, or summaries, based on simple instructions (often called “prompts”). Think of it as a digital assistant that can:
Draft documents
Summarise reports
Generate ideas
Analyse information
Generative AI can create content such as text, images music and video. For nonprofits, this means less time on admin and more time focused on impact and mission.
Where AI is Already Helping Charities?
Before diving into how to start, it helps to see where AI is already making a difference:
Writing funding applications
Creating donor communications
Analysing data and reports
Automating admin tasks
Supporting service users via chatbots
How Nonprofits Can Get Started (With Real Examples & Tools)
This is where many organisations get stuck. So let’s make it practical.
1. Start with Grant Writing (High Impact, Low Risk)
Grant writing is one of the easiest and most valuable entry points for AI.
What AI can do:
Draft first versions of applications
Reword content for different funders
Summarise organisational impact
Align proposals to funder priorities
Grantable is a lesser known, AI-tool that is purpose-built grant writing assistant that helps nonprofits draft, refine, and organise funding applications faster by generating proposal content, reusing previous responses, and aligning answers to funder requirements. Google Gemini can also help charities draft grant applications, summarise funder requirements, brainstorm project ideas, and rewrite content in different tones or formats. You can use the popular tools, such as ChatGPT or Microsoft Copilot, to draft and refine applications.
Example workflow:
1. Paste a funder brief into the AI engine of your choice
2. Ask: “Draft a response aligned to these priorities using our mission”
3. Edit and personalise (human review is essential)
One important note is that many grant providers use AI tools to determine if an organisation has specifically used AI to assist with their application and this can often lead to disqualification or non-interest. It’s extremely important that you do not just use the information provided by the AI tool alone and re-word any important section to humanise them. Personalisation is Key.
2. Automate Donor Communications
Fundraising can be time-consuming so there are some important AI tools available to help you streamline operations What AI can do:
Write tailored donor emails
Segment messaging by audience
Generate campaign content
Hubspot is an AI-powered email and campaign tool which could be extremely helpful in planning your sends and posts. You can draft and schedule your posts together, which can free up other time for other actions, such as being flexible for more reactive or urgent sends. Mailchimp is also another useful option as an AI content assistant. Mailchimp is primarily focused on email marketing and simpler campaign management, while HubSpot is a broader CRM and marketing platform that includes advanced automation, donor/customer tracking, and sales-style relationship management features.
3. Save Hours on Admin and Internal Work
Admin is one of the biggest hidden drains on nonprofit capacity. With the large majority of organisations relying on volunteer-led activity,, AI can be used effectively to streamline work and create impact in volunteer- restricted working days. What AI can do:
Summarise meetings
Turn notes into reports
Create agendas and action lists
Otter.ai is a great tool for helping with creating automatic meeting notes. It’s perfect for returning to later and even more beneficial for employees or volunteers to catch up on important updates they may have missed. Microsoft Copilot also has a great feature that can summarise documents in Word and Outlook. Notion AI is another useful tool for providing summaries on internal documentation.
Example Prompt: Upload a 10-page report and ask: “Summarise key insights and recommended actions for trustees”
4. Create Content Faster (Without Losing Quality)
Content creation is one of the most common AI use cases in charities. What AI can do:
Draft blogs and newsletters
Generate social media posts
Repurpose existing content
Google Gemini can help charities brainstorm blog ideas, rewrite content for different audiences, summarise long reports into shorter articles, and generate multiple versions of social media copy quickly. Canva is a fantastic AI design tool that can be used for social media posts, creating vibrant visuals, as well as presentations. Grammarly is also another useful tool to help with tone, provide clarity improvements and easily fix grammar mistakes.
Example Prompt: You could use prompts such as ‘Turn this into a 500-word blog post’ or set the tone by inputting ‘Use a warm and engaging tone aimed at supporters of a UK charity’
5. Support Service Delivery
AI isn’t just for internal work, it can also improve how you support beneficiaries. What AI can do:
Answer FAQs
Translate content
Simplify complex information
Orgnisations, such as Intercom, can provide AI chat support to provide instant responses to common questions, guide beneficiaries or donors to relevant information, reduce pressure on staff teams, and offer 24/7 support outside normal working hours. Whilst Google Translate can provide further accessibility to your organisation and provide communication in multiple languages.
Example Prompt: “Rewrite this housing policy in plain English for service users”
6. Common Pitfalls to Avoid
Even though adoption is high, many organisations struggle to get real value. Organisations don’t have a clear AI adoption strategy and use AI randomly, which limits the impact. Many teams or users do not feel confident using AI tools effectively or are wary of the negative implications of AI usage, leaving nonprofits without any AI policies in place. Here are some simple suggestions on how to tackle these scenarios:
No Clear Strategy: Focus on one or two high-value use cases first and form the strategy based on the steps you take and experience from them
Lack of skills and confidence: create and provide short, practical training
No AI policy: Start simple, don’t input sensitive data, always review the outputs and be transparent with your AI use.
How to Build Staff and Volunteer Confidence in Using AI Effectively and Responsibly
One of the biggest barriers to AI adoption in nonprofits is not the technology itself, butconfidence. Many staff and volunteers are unsure what AI should be used for, whether they are “allowed” to use it, or how accurate and trustworthy the outputs really are. Others worry about ethical concerns, data privacy, or the fear that AI could eventually replace jobs. These concerns are understandable, particularly in charities and civil society organisations where trust, safeguarding, and accountability are central to everyday work.
The good news is that building confidence does not require everyone to become an AI expert. In most cases, nonprofits simply need to create an environment where people feel safe experimenting with AI tools, supported when learning, and clear about the boundaries for responsible use. Introducing AI through practical, everyday tasks is often the most effective approach. Rather than presenting AI as something overly technical or futuristic, organisations should demonstrate how it can help with familiar tasks such as drafting emails, summarising meeting notes, brainstorming campaign ideas, or simplifying complex reports. When staff see AI helping with real problems they already face, confidence grows naturally.
Providing basic AI literacy training is also important. Staff and volunteers do not need deep technical knowledge, but they do need a foundational understanding of how generative AI works, what its limitations are, and why human oversight still matters. Short, practical training sessions can help demystify AI and reduce anxiety around using it. This should include guidance on writing effective prompts, checking for inaccuracies, and understanding common risks such as misinformation or bias.
Clear governance can also significantly improve confidence levels. Many people hesitate to use AI simply because there are no organisational guidelines in place. A simple AI policy helps staff understand what is acceptable and what should be avoided, particularly around sensitive information and data protection. Nonprofits should encourage experimentation while also reinforcing responsible practices such as fact-checking outputs and avoiding the use of confidential beneficiary data in public AI tools.
Peer learning can be used as a valuable tool. In many organisations, people feel more comfortable learning from colleagues than through formal training programmes. Identifying a few enthusiastic staff members or volunteers as internal “AI champions” can help encourage wider adoption by sharing tips, examples, and successful use cases across teams.
Some practical ways organisations can build confidence include:
Running informal AI workshops or “lunch and learn” sessions
Creating simple internal AI usage guidelines
Encouraging teams to test AI on low-risk tasks first
Sharing examples of time saved or improved workflows
Identifying internal “AI champions” to support colleagues
It is equally important for nonprofits to talk openly about the ethical and practical risks associated with AI. Discussions around bias, accessibility, environmental impact, GDPR compliance, and misinformation should form part of the conversation from the beginning. Responsible AI adoption should align closely with an organisation’s mission and values, rather than being treated purely as a productivity exercise.
Ultimately, confidence comes before transformation. The organisations seeing the greatest success with generative AI are not necessarily the most technologically advanced.They are the ones creating supportive learning cultures where staff and volunteers feel empowered to experiment responsibly. By starting small, focusing on practical use cases, and encouraging continuous learning, nonprofits can build the confidence needed to use AI effectively, responsibly, and in ways that genuinely strengthen mission impact.
Final Thoughts: Start Small, Think Big
Generative AI isn’t about replacing people, but about freeing them to focus on what matters most. For nonprofits, that means more time for beneficiaries, better use of limited resources and greater overall impact
The key takeaway? Start small, but start now, because the organisations that learn early will be the ones that benefit most.
Further Reading & Sources
Your Feedback Matters
What did you think of this text? Take 30 seconds to share your feedback and help us create meaningful content for civil society!
This piece of resource has been created as part of the AI for Social Change project within TechSoup's Digital Activism Program, with support from Google.org.
AI tools are evolving rapidly, and while we do our best to ensure the validity of the content we provide, sometimes some elements may no longer be up to date. If you notice that a piece of information is outdated, please let us know at content@techsoup.org.
This content was created with AI assistance and has been reviewed and edited by Seema Hassan