How to Use AI to Accelerate Fundraising for Charities

Top 10 Ways to Cut Costs and Boost Fundraising Impact with AI.

Introduction

Artificial Intelligence (AI) is rapidly transforming how charities engage supporters, raise funds, and optimise operations. With donor participation under pressure and resources stretched thin, AI offers charities the chance to automate tasks, personalise donor experiences, and achieve more with less. This insight explores ten practical ways AI can accelerate fundraising for charities, with real-world examples, tools, and analysis.

It’s useful to evaluate AI’s role in charity fundraising first through a quick SWOT analysis – examining Strengths, Weaknesses, Opportunities, and Threats. This provides a balanced view for the decision-makers on AI adoption.

SWOT Analysis: AI in Fundraising

Strengths

• Automates routine tasks → saves time & costs
• Data-driven decisions improve campaign targeting
• Personalisation at scale increases donor response & retention
• Boosts the efficiency of digital fundraising platforms

Weaknesses

• Dependent on quality donor data (garbage in, garbage out)
• Staff need training & confidence to use tools effectively
• Risk of generic or inauthentic messaging if over-reliant on AI
• Smaller charities may struggle with upfront setup or costs

Opportunities

• New channels (chatbots, voice assistants, virtual events) to reach donors
• Improved donor journeys & engagement → stronger loyalty
• Scalable personalisation & predictive analytics raise ROI
• Potential for collaboration, shared AI tools, and funder support for innovation

Threats

• Data privacy & GDPR compliance risks
• Algorithmic bias could exclude or mis-target donors
• Donor trust issues if AI use feels impersonal or hidden
• Rapid tech changes → risk of obsolete tools or wasted investment

In summary, the SWOT breakdown shows that AI’s value to fundraising is compelling (strengths/opportunities), but to fully realise it, one must address the internal challenges and external risks (weaknesses/threats). Strategies to maximise success might include: investing in staff training (to mitigate skills gaps), developing clear AI ethics policies (to guide usage and avoid pitfalls), and choosing projects with strong ROI and manageable risk to start. 

The good news is that many challenges (like tool selection, training) are solvable with planning and potentially support from partners or funders. And many threats (like privacy) can be mitigated by following best practices and legal guidance.

For CEOs and Marketing Directors evaluating AI, the key takeaway is that the value proposition is significant – higher revenue, lower costs, better donor relationships – but it comes with responsibilities. 

Governance and strategy must evolve alongside tech adoption. If done thoughtfully, AI can be a powerful asset in a nonprofit’s fundraising strategy, as numerous early success stories attest, while navigating the risks will ensure it serves the mission ethically and sustainably.

Ten Use Cases of AI in Fundraising

Fundraising in the charity sector is facing unprecedented challenges. Donor participation has been declining – in England, the proportion of people giving to charity dropped from 82% in 2013/14 to about 67% in 2023/24 – even as needs and competition for funds rise. 

With economic pressures like the cost-of-living crisis squeezing donors and charities alike, non-profit leaders are seeking innovative ways to do more with less. One emerging solution is artificial intelligence (AI). In fact, 76% of charities are now using some form of AI tool (up from 61% just a year prior), signalling a sector-wide recognition that AI can be a game-changer.

AI can help charities automate routine tasks, personalise donor engagement, save costs, and communicate more effectively, ultimately accelerating fundraising outcomes. This isn’t about robots taking over for fundraisers – it’s about augmenting human teams with smart tools to raise more funds and build stronger supporter relationships. 

Below, we explore ten key areas where AI can boost charity fundraising, with real examples, supporting companies/tools, and analysis of the benefits (and hurdles) for each. We’ll also glance at future trends so charity CEOs can weigh the value of AI adoption.

1. AI Chatbots for Donor Engagement & Support

AI-powered chatbots can serve as virtual assistants on a charity’s website or social media, handling inquiries from donors, beneficiaries, or volunteers instantly, 24/7. These bots simulate human-like conversations to answer FAQs, help visitors navigate donation pages, and even tell stories about the charity’s work. The immediate benefit is improved supporter experience – people get answers or guidance in seconds rather than waiting for an email or call back. This real-time engagement can keep potential donors from drifting away.

Crucially, chatbots also save staff time and operational costs. By automating interactions, they reduce the workload on human support teams. Studies show that AI chatbots can handle 60–80% of common questions instantly, freeing up staff for complex issues. For example, the UK fundraising platform Easyfundraising implemented an AI-based support chatbot and successfully offloaded 80% of support queries to AI – only the edge cases get passed to their human team. This kind of efficiency gain is money saved, which can be redirected to core mission activities. Additionally, donors get faster responses, boosting satisfaction and trust.

Real-world examples in the charity sector illustrate the range of what chatbots can do:

Example 1 – WaterAid’s Facebook Messenger Chatbot

WaterAid created an interactive storytelling bot that connects users with “Sellu,” a farmer in Sierra Leone, sharing his daily life and how donations help his community. This immersive experience kept users engaged through rich content (videos, photos, Q&A), strengthening their emotional connection to the cause. While it wasn’t directly soliciting donations, it educated and inspired supporters, which can lead to repeat donations from a more informed donor base.

Example 2 – Shelter Scotland’s “Ask Ailsa” Bot

Shelter Scotland faced a problem where 50% of helpline calls weren’t getting through, and their small team was overwhelmed.. They developed a chatbot (initially a hackathon prototype named “Sheldon,” later an implemented bot called Ailsa) to answer frequently asked questions about housing rights. The bot provides quick advice to people in need and collects initial information, thus streamlining service and reducing strain on staff. This not only helps those seeking assistance but also means donor funds can be used more efficiently since staff can handle more cases with the bot triaging basic queries.

Example 3 – Mencap’s Website Chatbot

The UK charity Mencap deployed a chatbot on its site as part of a campaign to dispel myths about learning disabilities. It uses a decision-tree style Q&A to inform and educate visitors. Engagement levels were high among those who used it, and Mencap reported a 3% increase in overall awareness of the charity, attributing some credit to the chatbot’s interactive education approach.. This demonstrates that chatbots can also play a role in marketing and outreach, indirectly supporting fundraising by widening a charity’s audience and impact.

From a digital marketing perspective 

Chatbots are valuable for handling inbound communication on channels like a charity’s website, Facebook Messenger, WhatsApp, or other social platforms. They ensure that whether someone asks “How do I donate?”, “Tell me about project X,” or “Can I fundraise for you?”, they get an immediate answer that can guide them to the next step in the funnel. In e-commerce terms, think of a chatbot as reducing drop-off on your donation page – by catching questions or hesitations in real time, thus improving conversion rates for donations.

Tools and Companies

There are many AI chatbot platforms available, and implementing one has become easier (often not requiring coding skills). For instance, Robofy (robofy.ai) offers an AI chatbot service tailored for non-profits to help automate donations and volunteer management, complete with a 14-day free trial. Its chatbots can provide instant responses, manage donation processing, and handle multiple inquiries at once, ensuring no supporter is left waiting. 

Other options include using mainstream AI chatbot builders like IBM’s Watson Assistant or Google’s Dialogflow, which some charities configure with their FAQs. Some providers even have free or discounted plans for non-profits – e.g., the chatbot platform at Chatbot.com advertises a free plan for non-profit organisations. This means even smaller charities with limited budgets can dip their toes into chatbot technology without huge upfront costs.

Cost Considerations

The cost of a chatbot can range from free (for basic versions) to monthly subscriptions of varying levels, depending on the complexity and volume of conversations. Many charities start with simple rule-based bots (which are cheaper) and then incorporate more advanced AI/NLP (natural language processing) as they grow. 

The development effort is typically in preparing the knowledge base (i.e., what information the chatbot will provide). Once set up, the marginal cost of each additional conversation is low, making it a scalable solution. When weighing cost, consider that the ROI comes in staff hours saved and potentially donations not lost. If a chatbot even helps convert a few extra donors or retains donors through good service, it likely pays for itself.

In summary, AI chatbots are a practical starting point for charities to automate engagement. They enhance donor experience through instant, around-the-clock support and narrative engagement, while simultaneously reducing costs on the charity’s side. For departments like supporter services, volunteer coordination, or digital marketing, chatbots can handle the repetitive inquiries and let staff focus on high-value interactions – ultimately accelerating the fundraising engine by building goodwill and trust with supporters at scale.

2. Hyper-Personalised Donor Outreach with AI

One of AI’s most powerful contributions to fundraising is the ability to personalise donor communications at scale. Donors are far more likely to respond to messages that feel relevant to them – that reference causes they care about, acknowledge their history with the charity, or match their preferences. Traditionally, segmentation and personalised marketing were done manually or with basic rules (e.g., grouping mailings by donation size or region). AI takes this to the next level by analysing huge amounts of donor data to find patterns and tailor messaging for each individual or micro-segment.

What AI-Powered Personalisation Looks Like 

AI can crunch data from your CRM – donation history, event attendance, email opens/clicks, demographic data, etc. and create very nuanced donor segments or even “segments of one.” It can then help generate content targeted to each segment. For example, AI might identify a group of lapsed donors who used to give to emergency appeals and craft a specific message to re-engage them, highlighting a new emergency campaign similar to what they supported before. 

Another group might be long-term monthly givers who care about impact metrics; they could receive an email with personalised impact stats (“Your donations have provided 50 meals…”). This level of personalisation can now be automated, whereas doing it manually for thousands of donors would be impossible.

Example 1 – Hyper-Personalised Outreach

A standout example of hyper-personalised outreach is the Ramadan 2024 email campaign by a Muslim Charity in the UK, in partnership with a tech firm called Giving Analytics. Facing the challenge of donor inboxes flooded with charitable appeals during Ramadan, they decided to try something bold: every donor received a unique email, generated by AI, that spoke in depth about that donor’s own relationship with the charity. 

Using Giving Analytics’ advanced segmentation and Large Language Model (LLM) integrations, they pulled in data like each donor’s past donations, interactions, and the specific impact of their contributions, and the AI composed individualised narratives for each donor. The result? This hyper-personalised approach boosted donations by over 300% compared to their standard campaign the previous year. 

In fact, they saw roughly a 4× increase in donations per email open (a 311% increase), and zero emails were marked as spam – indicating donors were highly engaged with content that didn’t feel like mass marketing. This campaign was so successful that it won the 2024 “Most Powerful Insight using AI/ML” award and the National Fundraising Award for Innovation, and it’s now held up as a prime example of how AI can transform fundraising communications.

The Muslim Charity case highlights several benefits of AI-driven personalisation:

• It grabbed donors’ attention because each message was uniquely relevant. Donors saw reflections of their own journey (e.g., “you started supporting us in 2018, and last year your generosity helped build 2 wells in Yemen…”), which is very compelling.
  
• It improved email performance metrics and ultimately revenue (tripling donations). This is consistent with marketing research that personalised emails can significantly outperform generic ones.
  
• It maintained regulatory and ethical standards – even with strict data protection, they were able to use data responsibly to enhance supporter experience. In fact, the positive donor feedback from this campaign showed that when done right, personalisation is seen as value-added, not an invasion of privacy.
  

Example 2 – AI-Driven Donor Segmentation

Many charities use AI-driven segmentation in regular appeals. For instance, an AI might segment a mailing list by predicted donation amount and then generate different ask strings for each segment (a major donor gets asked for a higher amount and shown a project that needs large funding, whereas a smaller donor gets a modest ask tied to a smaller project). This kind of fine-tuning can increase the likelihood of donation because the “ask” is just right for each donor. 

According to Fundraise Up, using AI to determine the “sweet spot” for donation requests – based on donor behaviour and non-personal data – helps ask for amounts that make sense for each donor, thereby increasing positive responses in fundraising pushes.

Tools and Support

A number of companies provide AI tools for non-profit personalisation. We mentioned Giving Analytics in the Muslim Charity example – they specialise in leveraging AI and segmentation for charities. Gravyty (gravyty.com) is another, known for AI-generated donor outreach emails; it integrates with CRMs and drafts personalised email messages to donors, learning a fundraiser’s style over time to sound authentic. Gravyty’s tool can even suggest which donors a fundraiser should contact each day and provide a tailor-written message for each, essentially acting like a personal assistant. 

On the more common software side, mainstream CRM platforms are adding AI features: for example, Salesforce Non-profit Cloud has “Einstein” AI that can analyse donor engagement and recommend whom to target next, and Blackbaud’s fundraising suite has introduced AI-driven donor insights as well. Even email marketing tools like Mailchimp or HubSpot have begun offering AI segmentation and content suggestions (HubSpot’s AI, code-named “Breeze,” can help craft and target messages). These tools can support marketing departments in executing personalised campaigns without needing data scientists on staff.

Digital Marketing Perspective

Personalisation primarily benefits the fundraising and marketing teams. Fundraising executives and donor communications managers will use AI insights to plan campaigns (deciding which cohorts get which messaging). Marketing/content teams then use AI content generation to draft the tailored messages, as we’ll discuss more in the content section. 

The donor database/CRM manager might work with data and AI outputs to continuously refine segmentation. Importantly, personalisation can also improve digital fundraising on websites – e.g., AI can customise the content a donor sees on a landing page if it recognises them as a repeat visitor, perhaps highlighting the program they last donated to. This crosses into the realm of e-commerce personalisation, which has been shown to boost conversion rates in online retail and, similarly, can boost donation conversion.

Challenges and Hurdles 

Implementing this level of personalisation isn’t without effort. Charities need to ensure their donor data is clean and well-structured to feed the AI (garbage in, garbage out). They also must be mindful of privacy – using data in ways that donors are comfortable with and that comply with GDPR or other regulations. In the Muslim Charity campaign, they worked within data protection confines and still achieved great results, showing it’s doable. 

Another hurdle is content volume: creating unique content for thousands of donors is exactly where AI helps, but staff still need to oversee it. Muslim Charity’s team, for example, tested outputs from multiple AI models to ensure quality and tone, essentially A/B testing the AI’s work. This indicates the need for a human in the loop to review and edit AI-generated messaging.

ROI and Value 

The ROI on personalisation can be very high – as seen, a quadrupling of donations in one case. Even less dramatic improvements, say a 10-20% increase in response rate, can mean tens of thousands more in donations from a campaign with no extra marketing spend on list acquisition. The cost side includes either subscription fees for AI tools or consulting fees (some charities might hire a consultancy like Wood for Trees or Giving Analytics for a specific project). 

Those costs can range from a few thousand pounds for a one-off project to ongoing SaaS fees (some CRMs charge extra for AI features). However, the Muslim Charity’s collaboration paid for itself quickly with the surge in donations, and other charities have reported that AI-driven campaigns often recover the investment in the first run. Also, note that some AI personalisation can be built using open-source tools for larger NGOs with tech capacity, potentially lowering cost.In summary, AI-driven hyper-personalisation allows charities to treat each donor as a unique individual at scale, which is the holy grail of donor communications. Done well, it boosts engagement, increases donation conversion, and builds stronger donor loyalty, because supporters feel seen and valued. This approach turns the data charities already have into actionable insights and tailored content – a clear win for fundraising effectiveness in the digital age.

3. Predictive Analytics for Targeted Campaigns

Wouldn’t it be helpful to know which donors are most likely to give before you even run a campaign? Or to predict which lapsed donors might return if asked a second time? This is where predictive analytics comes in. 

By analysing historical data and patterns, AI can forecast donor behaviour and campaign outcomes, allowing charities to target their fundraising efforts much more efficiently. In essence, predictive analytics uses machine learning to answer questions like: Who is likely to donate (and how much)? Who might become a major donor? Which donors are at risk of stopping their support? What type of campaign will perform best this season? Armed with these insights, fundraisers can prioritise their time and resources for maximum impact.

How It Works 

AI models (often machine learning classifiers or regression models) are trained on a charity’s data – for example, all the attributes of past donors and whether they donated in response to various appeals. The model learns which factors correlate with giving. It might learn, for instance, that donors who attend events and open 50% of emails have a high likelihood of donating above $500 in the next appeal. 

It might also learn external trends (maybe linking economic indicators or social media activity with giving patterns). Once trained, the model can score current donors or prospects on their probability to take a certain action (donate, upgrade to monthly giving, leave a gift in will, etc.). Fundraisers then use these “propensity scores” to tailor their approach – perhaps sending a personal letter or making a phone call to those with the highest likelihood, while sending cost-effective emails to mid-likelihood folks, and not spending limited resources on unlikely donors.

Benefits 

The benefit is a higher return on fundraising campaigns – you’re essentially using data to bet on the winners. It also helps discover opportunities and avoid missed ones. For example, AI might flag a donor with moderate past donations but high predicted capacity (perhaps their wealth indicators or engagement suggest they could give a major gift) – that’s a cue to a fundraiser to cultivate that relationship more. Conversely, predictive models can prevent wasted effort, like mailing expensive brochures to people who are very unlikely to give.

Example 1 – Real-World Success – Parkinson’s UK Case

A powerful case study is Parkinson’s UK, a large UK health charity, which worked with a data science consultancy (Wood for Trees) to boost its direct mail fundraising using predictive modelling. They traditionally used a segmentation approach (like many charities do): mailing people based on simple criteria (e.g., donated in the last 24 months, gave to a similar appeal before, etc.). Wood for Trees developed an AI-driven predictive model that scored each supporter’s likelihood of responding to a cash appeal. 

When Parkinson’s UK used this model for a mailing, the results were outstanding: it generated over £485,000 in total donations, with £405,000+ being net revenue after costs. In other words, the model identified donors who were “on the fence” or previously ignored by broad segmentation, and by mailing them with the right ask, the charity raised nearly half a million pounds extra. The development costs were covered in the first deployment of the model, proving the ROI. The model effectively activated or reactivated supporters who would have been overlooked, making the campaign far more lucrative than past approaches. This demonstrates how predictive analytics can uncover hidden gold in a donor database – people who have the capacity or propensity to give that wasn’t obvious through traditional methods.

Example 2 – Greenpeace Australia Donor Retention

Greenpeace Australia used an AI tool (by Dataro) to predict which of their monthly givers were likely to cancel (churn). By focusing their retention calls on those high-risk donors, they managed to retain an estimated 64 donors in one month, saving roughly A$23,000 in revenue that would have been lost. The campaign’s ROI was calculated at 2.13 (i.e., every $1 spent on the outreach yielded $2.13 in retained donations). Another non-profit using the same approach saved 296 regular givers and achieved a 3.19 ROI on their campaign.

These outcomes underline that predictive analytics isn’t just about immediate fundraising asks, but also about sustaining donor relationships for the long term – which greatly boosts lifetime value.

Beyond direct mail or calls, predictive models can also inform digital campaigns. For instance, an AI might predict which website visitors are most likely to donate (based on their browsing behaviour) and trigger a specific call-to-action for them (like a pop-up or a chatbot prompt), akin to how e-commerce sites personalise for likely buyers. Or it might predict which social media followers could become donors, helping target ads more efficiently.

Tools and Companies

Specialised fundraising AI providers offer predictive analytics as a service:

• Dataro (dataro.io) – provides machine learning software for non-profits to predict things like churn, upgrade likelihood, and campaign response. They share case studies (like those above) and typically integrate with CRMs to continuously score donors.
  
• DonorSearch AI – known for predictive philanthropy analytics, often used for major gift prospecting by analysing wealth and philanthropic data to suggest who in your database (or outside it) could be a major donor.
  
• Blackbaud’s NXT Intelligence – Blackbaud’s CRM for non-profits includes built-in predictive models (for example, it has a built-in “Likelihood to Give” score).
  
• Salesforce Einstein for Non-profits similarly offers predictions, such as likelihood to donate again, to help prioritise contacts.
  
• AI development agencies (like the Wood for Trees example) can build custom models for a charity if a tailored approach is needed.
  

For charities that have data science capacity, using open-source machine learning libraries (like Python’s scikit-learn or TensorFlow) is also an option, though this requires in-house expertise. Interestingly, there are also collaborations forming in the sector (e.g., through the Fundraising.AI initiative) to share knowledge on ethical AI use in fundraising.

Digital Marketing Departmental Implementation

Typically, the data/insight team or a tech-savvy fundraising analyst would work with these predictive tools. They translate the model outputs into plain-language recommendations for the fundraising team. For instance, the analyst might say: “Our model predicts 500 specific donors are most likely to respond to the spring campaign – let’s send them personal letters, and treat the rest with our usual email.” 

The direct marketing team then uses those lists, and the major donor team might get a list of 20 prospects to cultivate more deeply. Predictive analytics thus becomes part of campaign planning, donor pipeline management, and even budgeting (predicting revenues).

Challenges 

One challenge is ensuring the model remains accurate and up-to-date. Donor behaviour can change (especially in turbulent times like economic downturns), so models need retraining and monitoring. Also, algorithms can sometimes be a “black box” – fundraisers might be wary of trusting a prediction if they don’t understand it. 

Good practice is to validate predictions with small tests (e.g., do a test mailing to high-score vs low-score donors and see the difference). When Parkinson’s UK tried their model, it was likely after some pilot to prove it beats the old segmentation. 

Another concern is bias: if the data reflects historical bias (say, always focusing on older donors), the model might overlook younger donors just because they haven’t given before – potentially a missed opportunity or an unfair assumption. Ensuring the AI is used to broaden outreach, not narrow it unjustly, is important (some models incorporate look-alike data to find new prospects that resemble your donors, which can diversify outreach).

Cost and ROI

The cost for predictive analytics tools can vary. Some, like Dataro, operate on subscription (possibly a few hundred to a few thousand dollars a month, depending on org size). Others might take a percentage of funds raised (though that’s less common). As shown, the ROI can be very high – Parkinson’s UK’s £405k net gain is huge, and even smaller scale, a few extra donors retained can justify the cost. 

It’s often about scale: larger databases have more to gain and can spread the cost. However, even mid-size charities are using simpler predictive tools (like churn scoring) with success. Notably, as these AI tools become more common, the cost is gradually coming down, and open-source or DIY options exist for those with skills, making it accessible even to resource-strapped nonprofits.

In summary, predictive analytics allows charities to fundraise smarter by using data to anticipate where their efforts will pay off best. It’s like having a data-informed compass for your campaigns. By focusing on the right donors with the right ask at the right time, charities can significantly improve their fundraising outcomes and avoid both the cost and donor fatigue associated with less targeted mass appeals. 

This strategy, complemented by the personalised approaches discussed earlier, creates a one-two punch: you first predict who and how to ask, then personalise the ask for maximum effect. Together, they can dramatically accelerate fundraising success.

4. AI-Optimised Donation Platforms and Conversion

In the realm of digital fundraising, the donation experience itself – the ease of giving on your website or app – plays a huge role in conversion rates and donor satisfaction. AI has begun to revolutionise this aspect by making online giving more personalised, seamless, and even fun. 

We can draw parallels to e-commerce checkout optimisation: just as Amazon uses AI to reduce cart abandonment and increase purchase size, charities can use AI to reduce donation form abandonment and increase donation amounts or recurring gifts. This is done through AI-optimised donation platforms and smart payment processing.

One prominent example is the rise of intelligent donation forms, such as those provided by Fundraise Up (a fundraising platform used by many non-profits). Fundraise Up uses AI and machine learning to adapt and optimise the donation process in real-time. Some features include:

• Smart Donation Suggestions: Instead of static suggested giving amounts, AI analyses hundreds of data points about the donor’s behaviour (and sometimes aggregated data from similar donors) to suggest an “optimal” donation amount for that individual. For instance, if a donor frequently gives £50, the form might suggest £60 as a slightly higher contribution that data indicates they might be willing to consider. Fundraise Up reports that this dynamic personalisation results in a 10–15% increase in overall donation revenue for non-profits.
  
• Recurring Donation Prompts: AI can identify when to prompt a one-time donor to convert to a recurring donor. Rather than a generic “make this monthly?” checkbox, Fundraise Up’s system might time a prompt or frame it in a way that feels compelling based on the user’s behaviour. They found that about 2.3% of one-time donors convert into recurring donors with these AI-driven nudges – a small percentage that can have large lifetime value implications.
  
• Adaptive Fee Coverage: Many donation forms allow donors to cover the processing fee. AI can determine the best moment to ask this (for example, after the donor has decided the amount, feeling positive about their gift). By optimising this prompt, Fundraise Up sees 82% of donors agree to cover fees, which means more money goes to the charity net of fees.
  
• Intelligent Card Retries: Failed recurring donation payments (due to expired cards or transient issues) are a big source of lost revenue. AI can schedule retry attempts at times the data suggests they’ll go through (perhaps after a paycheck day, or at a time of day the bank systems have lower failure rates, etc.). This has been shown to significantly lower churn rates for recurring donations. Essentially, fewer monthly givers are lost due to payment failures, which preserves donor lifetime value.
  
• Real-time UX Optimisation: If a donor hesitates on a field, AI might simplify the form or offer help. Some platforms A/B test form layouts continuously using AI to maximise completions. Others use chatbots that pop up if you stay too long on a donation page, asking if you have questions – potentially rescuing donations that might have been abandoned.
  

From an e-commerce perspective, these are analogous to conversion rate optimisation techniques and upsells/cross-sells, but applied to fundraising. For example, suggesting a donation upgrade or a monthly gift is like an upsell, and prompting fee coverage is like an add-on sale (except it’s to cover a cost). In digital marketing terms, AI is helping increase the average “order” value and retention rate of donors.

Companies and Tools

Aside from Fundraise Up, other donation platforms incorporating AI include:

• GoFundMe Charity (and Classy): They have experimented with AI in peer-to-peer fundraising to suggest fundraiser tips or donation targets.
  
• Giving Block (for crypto) might not use AI in the same way, but as new tech in giving emerges, AI will likely optimise those flows too.
  
• Custom Solutions: Larger organisations sometimes build their own donation pages and use tools like Google Optimise (which has ML-driven personalisation) to test different page variants automatically, or they plug in recommendation APIs to suggest donation amounts.
  
• PayPal’s Donate platform uses algorithms (though proprietary) to suggest charities to donors and to enable one-click giving experiences. While not something a charity controls, it’s part of the AI influence in digital giving.
  
• Stripe (a payment processor) provides some smart retry logic for failed payments and fraud detection using AI, which helps ensure genuine donations go through and fraudulent ones are blocked – protecting revenue and donor trust.
  

Cost and Implementation 

Many of these advanced platforms charge either a subscription or a percentage fee. For instance, Fundraise Up charges non-profits a platform fee (it may vary, but roughly it could be around 3.5% or a monthly fee plus a smaller percentage). At first glance, this is a cost, but since they often demonstrably raise more money (10-15% more as noted), the net is still positive. 

In fact, some non-profits reported that after switching to an AI-optimised platform, their increased revenue far exceeded the fees, essentially making it a self-funding improvement. There may be some setup effort to integrate these platforms into your website and CRM, but they are designed to be relatively plug-and-play for a digital team (often with just a snippet of code or a WordPress plugin).

Another angle is A/B testing with AI: In traditional donation form optimisation, you might test one form vs another manually. AI can accelerate this by trying many micro-variations and using multi-armed bandit algorithms to serve the best option more often. This means over time, the form “learns” to be the most effective for your audience. That’s not something a single fundraiser could practically do on their own.

Digital Marketing Departmental Perspective

This area lies at the intersection of fundraising and digital product/IT. The digital fundraising or web team would typically lead the adoption of an AI-optimised donation platform. They care about metrics like conversion rate (what % of people who click “Donate” actually complete the donation) and average gift size. 

The marketing team also benefits since all the effort driving traffic (SEO, ads, email campaigns) yields better results if the landing page converts better, effectively improving ROI on marketing spend. E-commerce best practices (like reducing form fields, ensuring mobile-friendliness) are often baked into these AI-driven forms as well, so the charity’s online giving becomes modern and user-friendly, reflecting well on the brand too.

Donor Experience

Importantly, these AI enhancements often make giving easier and more satisfying for donors. Instead of being confronted with a one-size-fits-all form, donors might see a preset amount that “feels right” (reducing decision fatigue), an option to make it monthly (with the benefits explained), and a quick checkout process. 

A smooth experience can be the difference between a completed donation or an abandoned one, especially for new donors. There’s evidence in e-commerce that even a one-second delay or a slightly confusing form can drop conversions – likely similar in donations.

Results 

Fundraise Up shared that non-profits using their platform saw recurring donor retention at 76% over 12 months versus an industry average of 61% – that’s a notable jump, attributed to their suite of AI features keeping donors engaged and payments flowing. 

While individual results vary, numerous case studies show significant lifts in online fundraising after optimising the user journey with AI and best practices (double-digit percentage increases in revenue are not uncommon). For charities increasingly reliant on digital (especially after COVID-19 pushed more fundraising online), this is low-hanging fruit to accelerate income.

In conclusion, AI-optimised donation platforms tackle the crucial “last mile” of fundraising – getting the donation. By reducing friction, personalising asks, and preventing loss of donations (via retries and retention tactics), AI ensures that the hard work of engaging donors actually results in funds. 

It’s an area where marketing, psychology, and technology converge: understanding donor behaviour and using AI to respond in real-time. For any charity looking to boost online fundraising, investing in smarter donation tech can yield quick and substantial gains, effectively accelerating fundraising without needing to find new donors – simply by better serving the ones already at your (virtual) door.

5. Generative AI for Content Creation and Storytelling

Fundraising is fundamentally about storytelling and communication – inspiring people to care and give through narratives, imagery, and information. However, producing a steady stream of high-quality content (appeal letters, impact stories, social media posts, donor updates, campaign slogans, blog articles, videos, etc.) is labour-intensive. Many charities have small communications teams wearing multiple hats, making it challenging to keep content fresh and tailored to different audiences. 

Enter generative AI, which includes tools like OpenAI’s ChatGPT, Google’s Bard, and others. These AIs are essentially supercharged writing and creativity assistants that can generate human-like text (and even images or video to some extent) based on prompts. Used correctly, they can dramatically accelerate content creation for fundraising and marketing.

Think of generative AI as an “always-on copy assistant” that can help draft materials, brainstorm ideas, and refine messaging. Here’s how it can be utilised in the charity fundraising context:

• Appeal and Email Drafts: Need to write a fundraising appeal letter or email? AI can produce a solid first draft in seconds. For example, you could prompt ChatGPT: “Write a compassionate fundraising letter for a children’s charity, asking for £20 to provide school supplies, include a success story and a call-to-action.” The AI will generate a letter that you can then edit to add specific details or adjust tone. This can save hours that would otherwise be spent on a blank page. Teams are using this to create multiple versions for different segments: One AI prompt can output three versions of an email – say, one geared to new donors, one to regular givers, one to lapsed donors – each with appropriate tone and messaging.
  
• Social Media and Blog Content: Generative AI is great for repurposing content across channels. For instance, you have a donor story from your newsletter – AI can help turn that into a series of social media posts, each tailored to platform conventions (short and catchy for Twitter, a bit more narrative for Facebook, professional tone for LinkedIn). It can also suggest creative taglines or hashtags. If you need ideas for your next blog post or campaign theme, you can brainstorm with AI (“Give me 5 emotional story angles for a water charity campaign”) – it will produce suggestions that you can build on.
  
• Grant Applications and Reports: We touched on grants separately, but generative AI can assist by summarising data or formatting text. For example, if you paste a bunch of raw impact statistics or testimonials into the prompt, it can help weave them into a narrative paragraph for a report. It’s like having a junior writer or editor on call.
  
• Translations and Multilingual Outreach: For charities engaging donors in multiple languages, AI translation (via models like DeepL or Google’s advanced translation AI) can quickly convert content. While one should have a human native speaker review for nuance, it speeds up getting a base translation.
  
• Creative Content (Images/Video): While text AI is the most mature, there are AI tools like DALL-E, Midjourney (for images), or even basic video generators that can help create visuals. For example, a charity could use an AI image generator to create an illustration of a scenario (e.g., an AI-generated concept image of a new school building for a vision piece) rather than hiring a graphic designer. Some charities have even tested AI-generated photos in fundraising to see if they perform as well as real photos. The results of such tests are still emerging, and real stories/photos generally resonate strongly, but AI imagery could supplement when resources are scarce.
  

Time and Resource Savings

The biggest advantage is speed. A task that might have taken a team member all day can potentially be done in an hour with AI help. For example, the Lewis Gavin article (2025) notes that AI is about “supercharging small teams so they can produce better content with greater personalisation,” not about replacing human creativity. A human plus AI can produce more output than a human alone, which for a non-profit might mean going from sending one generic appeal to sending three tailored ones in the same time. It also means staff can iterate faster – test two versions of messaging and see which works, etc., since generating versions is easy.

Quality Considerations 

While AI can draft content quickly, it’s not perfect. It may need editing to ensure facts are correct and the tone aligns with your brand. AI might sometimes produce text that feels a bit formulaic or too “general.” That’s why it’s best seen as a collaborator: it gives you a base to work from. One effective workflow is to feed AI with specific info (e.g., “Here are 5 bullet points about our project impact… now turn this into a compelling story”). The output will include those facts woven into a narrative, which you can then personalise further. This ensures the content is both accurate and humanised. Many non-profits also establish guidelines or review processes for AI-generated content to maintain authenticity – for instance, requiring that a staff member who knows the donor audience well review and tweak anything before publishing.

Cost of Tools

Generative AI tools are actually quite affordable for the value they provide:

• ChatGPT – The basic version (GPT-3.5) is free to use. The premium ChatGPT Plus (which provides access to the more advanced GPT-4 model, faster responses, etc.) is $20/month. OpenAI also has an API where usage is pay-as-you-go (a few cents per thousand tokens of text, which is also inexpensive for typical needs). Importantly, OpenAI offers non-profit discounts for their enterprise plans, and organisations can apply for grants or subsidised access. So a charity could potentially leverage even advanced AI at reduced cost.
  
• Microsoft Copilot – This integrates with Office apps (Word, Outlook, Excel, etc.) and can generate content within those. It’s a paid add-on for Microsoft 365. However, registered non-profits can receive a $2,000 annual Azure/M365 credit, which can cover Copilot licenses or other AI services. This effectively makes that cost zero or very low for many organisations, at least up to that credit amount.
  
• Other Tools – Many other gen-AI writing tools exist (Jasper.ai, Copy.ai, etc.). Some have non-profit pricing, others are reasonably priced subscriptions. Given the competitive market, prices have been dropping, or tools are bundling more features for the same price.
  

Using AI does require a computer and internet (which is given for most office setups) and some staff learning. But many staff find tools like ChatGPT quite user-friendly after a short introduction.

Digital Marketing Departments and Use Cases

The communications and marketing team is the obvious beneficiary – those creating fundraising appeals, web content, social posts, newsletters, etc. But even beyond that: program teams might use AI to document stories from the field (write draft case studies), the CEO or leadership might use it to draft thought leadership pieces or speeches faster, and volunteers could be empowered to help with content if they have AI assistance (imagine volunteer fundraisers who can generate their own event promo copy using provided AI prompts). Essentially, it democratises content creation – you don’t have to be an expert copywriter to get a decent draft, which is helpful in charities where people often juggle multiple roles.

Maintaining Authenticity

One concern CEOs or fundraisers might have is: will AI-generated content sound robotic or insincere? The key is that the human guides the AI. You inject the heart by providing the anecdotes, emotions, and mission detail; the AI provides polish and structure. Also, newer AI models (like GPT-4) are quite good at producing empathetic and fluent text when guided. Many non-profit professionals have reported that with careful prompt design, AI can capture a tone close to what they want – and then a bit of human editing makes it indistinguishable from a fully human-written piece, except it took a fraction of the time.

Example Prompt & Result

A charityexcellence.co.uk guide gives an example prompt: “Create a list of 12 fundraising ideas that are simple and easy to do for a small UK charity.” In seconds, ChatGPT could list out 12 ideas (e.g., bake sale, sponsored walk, online raffle, etc., each with a short description). For a staff member, that might have taken a brainstorming session or research across several sites – AI speed it up. They also caution about limitations (ChatGPT’s knowledge cutoff, not browsing real-time info, etc., unless using connected tools). But these limitations are manageable (for current data, one could use Bing’s AI or wait for updated models).

In conclusion, generative AI is like an amplifier for a charity’s voice. It helps you produce more content, maintain a steady drumbeat of communication with supporters, and tailor messages to different platforms and audiences without requiring a large team of writers.

This directly accelerates fundraising because better and more frequent communication leads to better donor engagement and response. Whether it’s the moving story in an appeal or the catchy tagline of a campaign, AI can assist in crafting it. Of course, the human touch and strategic direction remain vital – AI is a tool, albeit a very powerful one, now accessible to even the smallest non-profits. Those who embrace it can gain a communications edge, producing quality fundraising materials that keep supporters inspired and informed, ultimately driving more donations.

6. AI Assistance in Grant Writing and Fundraising Proposals

Beyond individual donations, many charities rely heavily on grants – whether from governments, foundations, or large institutional donors. Writing grant applications and funding proposals is a specialised but time-consuming aspect of fundraising. Each proposal must be carefully tailored to the funder’s criteria, filled with data and narratives, and written compellingly. AI can significantly accelerate the grant writing process and improve the quality of proposals by acting as a drafting and research assistant.

Helping Draft Grant Proposals 

Microsoft’s “Copilot for Non-profits” and tools like ChatGPT can help grant writers draft sections of proposals or reports quickly. For example, suppose you need to write the “Need Statement” for a grant, describing the problem your project addresses. You can feed AI with key points or even ask it to pull from known data (“Use UN statistics on child literacy”, etc.) and get a solid paragraph or two that you can then refine. AI is especially good at structuring text, so it can ensure you have a logical flow: problem -> approach -> impact, etc., which you can then personalise.

Streamlining Research 

Often, grant writing involves researching stats or precedent projects. AI can accelerate this by summarising research reports or extracting relevant statistics if provided with documents (for instance, using AI to summarise a lengthy needs assessment study into bullet points you can quote). While one must double-check facts (AI can sometimes make errors if not given the sources directly), it speeds up the information-gathering step. There are even AI tools designed to search grant databases or match your project with potential funders, though those are more about research than writing.

Improving Clarity and Tone 

A common challenge is adjusting jargon and tone for different funders. AI can help rephrase complex program language into more accessible terms or vice versa (making a narrative more technical if needed). You could paste a dense technical paragraph and prompt, “Simplify this explanation for a general audience,” and the AI will output a clearer version. This ensures your proposal is easily understood by grant reviewers, which can increase success chances.

Reporting and Summaries 

After winning a grant, reporting back to the funder is another heavy writing task. AI can take raw monitoring and evaluation data and help craft a narrative report. For example, by inputting achievements vs targets, beneficiary quotes, and financial figures, AI can weave them into a first draft of a progress report, which you then fact-check and edit. This could cut down days of work, especially for nonprofits juggling multiple grants.

Example – Reddit User

A Reddit user in the non-profit space mentioned that “This year, 100% of our grant applications have been supported by AI. It’s a great tool for small orgs who don’t have a grant writer on staff”. While anecdotal, it highlights that some are already embracing AI to ensure even small teams can put out professional proposals. Another story: an Orr Group article noted that even a 10-20% reduction in time required per grant can allow an organisation to apply for more grants in a cycle, potentially increasing their funding pool (imagine writing 12 proposals a year instead of 10, just because you saved time on each).

Grant Writing AI Tools

Beyond general AI like ChatGPT,

• Grantable is an AI-based tool specifically for grant writing assistance. It helps outline proposals and can auto-fill repetitive sections (like organisational info, common language on mission, etc.).
  
• Foundation Directory AI (not exactly writing, but some tools use AI to help identify which grants you should pursue, saving time on targeting).
  
• Some CRM systems (e.g., Fluxx or Salesforce) might incorporate AI to manage grant calendars or draft emails to grantmakers.
  

Risks and Best Practices

Funders are starting to discuss AI-generated proposals. The concern is that if everyone uses AI, proposals might start to sound similar or be less authentic. Fundraising experts suggest using AI for the grunt work, but always adding your non-profit’s unique voice and specific details. For instance, AI might give a generic sentence like “Our project will significantly impact the community,” which you should enrich with specifics: “Our project will train 50 local youth, leading to a 25% increase in tech employment in the community, according to our pilot results.” 

AI can get the structure, but the insight and passion should come from you. Another best practice is to double-check that the AI hasn’t introduced any fictitious data (sometimes called “AI hallucination”). If you prompt an AI without giving it the data, it might make up a stat to seem helpful, which could be disastrous in a grant (imagine citing a stat that doesn’t exist). The key is to provide it with the points or ask it to only use the provided info or widely known sources.

Training and Team Adoption 

Not all grant writers are tech-savvy or trust AI out of the gate. Training sessions or sharing success stories can help. It’s worth noting that Microsoft’s non-profit offerings explicitly highlight grant writing as a use case for Copilot, meaning it’s recognised as a domain where AI adds value. Some charities have even run internal experiments, like writing one proposal “the old way” and one with AI assistance, then seeing if there’s a difference in quality or success. The goal is usually to free the human expert to do the higher-level work – strategy, relationship-building with funders, customising the narrative – rather than crunching out verbiage or repetitive text.

Value Proposition

The value of AI in grant writing can be summarised as more grants, better grants, with less burnout. If your team can crank out more applications, you increase your chances of funding. If those applications are clearly written and well-structured (as AI can help ensure), possibly your win rate goes up, too. 

And if staff are less stressed by looming writing deadlines, they can allocate time to reviewing and refining, which again improves quality. Also, consider small organisations or grassroots charities – they often skip applying for certain grants because they lack the capacity to write them. AI could level the playing field a bit, enabling them to put in applications they otherwise wouldn’t, unlocking new funding sources.

In summary, AI doesn’t replace the need for understanding your program and impact, but it takes on the heavy lifting of wording and formatting. For CEOs concerned about whether investing in such tools or training staff on AI is worth it: if a single additional grant is won thanks to AI-enabled efficiency, that could be tens or hundreds of thousands of dollars/pounds – a massive ROI. And even for grants not won, fewer staff hours spent per application saves salary costs that can be diverted to other fundraising work. Therefore, integrating AI into the grant writing process is a strategic move to accelerate institutional fundraising and ensure no opportunity is left on the table due to bandwidth issues.

7. Automating Administrative Tasks to Reduce Costs

Fundraising isn’t just glitzy galas and creative campaigns; a lot of it involves nuts-and-bolts administration. Processing donations, updating databases, generating receipts, handling donor inquiries, preparing reports – these routine tasks can eat up a huge portion of staff time. They’re necessary, but every hour spent on admin is an hour not spent on strategy or donor relationships. AI-driven automation, including both traditional Robotic Process Automation (RPA) and AI-enhanced workflow tools, can take over many of these repetitive tasks, saving costs and accelerating operations behind the scenes.

Streamlining Data Entry and Management 

Many non-profits still handle tasks like inputting donation data from multiple sources (online, events, bank transfers) into a central system. AI can help by either directly integrating systems or even literally “reading” documents. For example, AI-powered OCR (optical character recognition) can scan printed donation forms or bank statements and automatically update your CRM. 

Some organisations use RPA bots to log into systems and transfer data the same way a human would, but much faster and without errors. Qlic’s article notes that automating tasks like data entry, donor matching, and gift processing frees up staff for strategic initiatives. This means if you receive hundreds of donation records a week, an AI script could auto-match them to donors and flag any anomalies, instead of staff manually reconciling records.

Consistent Donor Communications

Automating email acknowledgements and receipts is another area. Most CRMs have that feature, but AI can enhance it by personalising the thank-you note content based on donation specifics (as discussed earlier with content generation) and scheduling it optimally. AI-driven marketing automation can ensure, say, a new donor immediately gets a tailored welcome series, without someone having to remember to send it. Campaign management can also be partly automated – scheduling social media posts, emails, and tracking responses can be set up once and then let run, with AI ensuring timing and segmentation are optimal.

Example – AI in Support & Inquiries 

We talked about chatbots for external engagement, but internally, think of AI agents that handle common donor emails. If donors email questions like “How do I update my credit card info?” or “Where do I find your annual report?”, AI could parse and send a friendly reply with the info or appropriate link. This is similar to chatbots, but via email. It’s doable with natural language processing that classifies incoming inquiries and either answers them or routes them to the right person. Given that charities often have lean teams, having an AI filter and handle a chunk of these inquiries (even if it’s just providing an initial helpful response) can reduce response times and workload.

Back-Office Paperwork 

Fundraising teams also deal with internal paperwork – drafting policies, risk assessments for events, volunteer guidelines, etc. Generative AI can create first drafts of internal documents as well. For example, an AI can draft a volunteer onboarding guide or a data protection policy tailored to a small charity, which staff then refine. This helps ensure necessary documentation is in place without pulling staff away for days to write from scratch.

Lewis Gavin’s piece on “Cutting Costs, Not Corners” emphasises that non-profits should ask, “Where are we spending time on things that could be done faster, smarter, or with less effort?”. Encouraging the team to identify such tasks can spark ideas that AI can likely tackle. Often, fundraising teams think certain chores “have to be done manually” because that’s how it’s always been, but modern AI tools or even basic automation can surprise you.

Tools and Platforms for Automation

• CRM Automation: Most donor management systems (Salesforce NPSP, Blackbaud, NeonCRM, etc.) offer workflow automation. AI plugins or logic can enhance these – for instance, auto-filling missing data (like adding titles or standardising addresses via AI address verification).
  
• Microsoft Power Automate / Flow: With a bit of configuration, this can connect apps (e.g., if someone fills a Google Sheet or Typeform, it triggers an action in Outlook or your database). Microsoft is adding AI builders to Power Automate that can read forms or categorise text.
  
• Zapier / Make (Integromat): These are user-friendly automation tools that can incorporate AI services (like using a Zapier integration to send text to an AI sentiment analysis or language tool and branch actions accordingly).
  
• AI Services: Specific ones like Azure Form Recognizer (to parse forms), Google’s Document AI, or UIPath (an RPA tool that has AI capabilities) are a bit more technical but powerful for heavy data tasks.
  
• Accounting and Reconciliation: While not always in the fundraising department, reconciling donation records with bank deposits can be automated. QuickBooks, Xero, etc., now have AI that matches transactions. This saves the finance team time, indirectly benefiting fundraising by giving them more accurate and timely financial information.
  

Impact on Costs

By automating repetitive tasks, charities can potentially operate with leaner staff or reassign staff to growth-oriented roles. For example, if AI automation reduces the need for a part-time data entry role, that budget could be reallocated to hire a fundraising officer who cultivates major donors – a better return activity. Or if existing staff free up 10 hours a week, that’s 10 hours that can go into writing grant applications or meeting donors. AI doesn’t necessarily mean cutting jobs; often in charities, it means expanding capacity without an equivalent budget increase. Given tight administrative budgets, this is crucial. Automation also tends to reduce errors (e.g., fewer typos in donor names or incorrect amounts), which maintains professional standards and donor trust.

Employee Satisfaction

On a qualitative note, staff are often happier when they’re not stuck doing mindless tasks all day. By letting AI handle the drudgery, you improve job satisfaction, which can reduce turnover. High turnover is a hidden cost in fundraising teams, so anything that helps retain staff (by letting them focus on rewarding parts of their job like strategy and relationship building) is valuable.

Considerations 

To implement automation, you sometimes need to map out your processes clearly. This exercise in itself is helpful – understanding your workflow makes it easier to spot inefficiencies. There might be an upfront time investment to set up automations and train the AI (or feed it historical data, etc.). Start small: maybe automate one task (like importing online donations into the CRM daily with an AI script). Once tested and reliable, move to the next. Gradually, you build a suite of background processes that run with minimal intervention.

In summary, AI automation is like the unseen engine tuning of a fundraising operation. It doesn’t directly ask for donations, but it makes the whole machine run faster and cheaper. Routine tasks get done in a flash, data is more accurate, and staff have more time for creative and strategic work, which in turn leads to raising more money. 

For charity leadership, investing in automation (or simply empowering your existing IT person to implement it) can yield one of the highest payoffs, because it continuously returns value once set up. It’s an area sometimes overlooked in the excitement of public-facing AI like chatbots, but it’s equally, if not more, important for sustainable fundraising growth.

8. AI-Powered Donor Retention and Engagement Strategies

Acquiring new donors is often more expensive than keeping existing ones. Thus, improving donor retention is a powerful way to boost fundraising (higher lifetime value, more reliable income). AI can play a pivotal role in keeping donors engaged and loyal by predicting and proactively addressing churn (donors stopping giving) and by personalising ongoing communication to maintain interest.

We touched on predictive analytics for targeting and identifying at-risk donors in Section 3. Here, let’s focus on how AI is used in practice to retain donors and deepen engagement.

Predicting Donor Churn 

Using machine learning, charities can analyse patterns that typically precede a donor lapsing. For example, a regular giver who hasn’t opened the last few emails or whose donation amount has slowly declined might be at risk. AI models assign a churn risk score to each donor. Armed with this, your team can take early action – like reaching out with a personal call or a special update to rekindle their connection. As mentioned, organisations like the Victor Chang Institute and Greenpeace used this approach to save hundreds of donors, translating to tens of thousands in retained revenue. By focusing retention efforts where they’re most needed, AI ensures you’re not scrambling reactively after donors have already left.

Personalised Retention Outreach

AI doesn’t just identify who is at risk; it can inform how to win them back or keep them. For instance, through sentiment analysis of donor feedback or surveys, AI might learn what concerns or interests different donor segments have. Maybe some donors value detailed impact reports, while others care about being thanked publicly. AI can help segment these preferences and automate the delivery of the right retention tactic. 

One nifty usage: if an AI notices a recurring donor has a card about to expire (payment likely to fail), it could trigger an automatic but friendly reminder for them to update their info – preventing an accidental churn. Fundraise Up’s intelligent systems do this kind of behind-the-scenes work to keep donors active, contributing to that higher retention rate (76% vs 61% industry), they noted.

Engagement Scoring and Next Best Action 

Similar to churn prediction, AI can score how engaged each donor is at any given time (based on recency of giving, event participation, website activity, etc.). Then it can suggest a “next best action” to deepen that engagement. For a highly engaged donor, it might be the right time to invite them to volunteer or visit a project (thus bonding them more to the cause). For a less engaged one, maybe send a heartwarming story or a survey asking for their input (people who feel heard often stick around). This is the kind of tailored journey design that AI can assist with. Some CRMs have begun to include “engagement journeys” that adapt based on AI analysis of donor behaviour.

AI-Driven Personal Touches

It sounds ironic – using AI to create personal touches – but it works when done right. For example, an AI could help draft a personalised thank-you note or check-in email for a long-term donor, highlighting something specific (like “It’s been 5 years since your first donation, and we wanted to share how much impact you’ve made…”). Gravyty’s tool can generate such emails for fundraisers, who can then send them individually. This way, donors receive timely, context-aware communication that feels personal – because it is, the data is about them, even if AI helped with the heavy lifting of writing it. Such gestures can significantly boost a donor’s feeling of connection and loyalty.

Keeping Content Relevant 

Another retention strategy is ensuring donors get content that aligns with their interests. If a donor gave to a “Clean Water” project, AI can tag them and ensure most communications they get are about clean water or related outcomes. As the charity does diverse work, AI can filter news so each donor isn’t bored or alienated by content they don’t care about. This is akin to content personalisation but focused on retention – keeping them interested so they continue giving. Over time, if their behaviour changes, AI detects that and updates what they receive.

Multi-Channel Engagement 

AI also helps coordinate engagement across channels (email, phone, social media, direct mail) to ensure donors feel consistently valued. For instance, if AI predicts a donor is about to lapse, it might suggest a multi-channel “save” strategy: an email sharing impact, followed by a tailored social media ad they’ll likely see, and if no action, a phone call. This approach, guided by AI but executed by humans and software, can gently pull a donor back in.

Volunteerism and Other Involvement 

Retention isn’t just about donations. If donors engage in non-monetary ways (volunteering, advocating), they often stick around as donors, too. AI can help identify who might be open to deeper involvement. For example, analysing a donor’s comments or survey responses, AI might flag that a certain donor has expressed interest in volunteering. The team can then reach out with that opportunity – strengthening the donor’s bond with the organisation. Strong bonds = long-term giving.

Digital Marketing Departmental Perspective 

Retention tends to be a focus for donor relations or stewardship teams. These are the folks writing thank-yous, calling donors on anniversaries, etc. AI is like a super-charged CRM assistant for them, telling them whom to prioritise today and even drafting some communications. It also involves the analytics team, as they set up the models, and the communications team for producing the content used in retention (like impact stories, newsletters). It’s a collaborative use of AI across the fundraising department.

Metric Improvements

The key metrics here are donor retention rate (what % of last year’s donors gave again this year) and donor lifetime value (how much a donor gives before they lapse). AI can help bump those numbers up. Even a few percentage points of improvement in retention can mean a big revenue difference year over year. For example, if you retain 5% more donors, that could translate to thousands of extra donations without expanding acquisition. It’s essentially making the leaky bucket less leaky, which is very cost-effective.

Example Outcome

The Dataro case studies gave concrete figures: one program saw 296 donors “saved”. Think about what that means – 296 people who likely would’ve stopped giving but didn’t. If each were giving, say, $20/month, that’s over $70k a year preserved. The ROI was 3.19, so definitely worth it. And beyond numbers, each retained donor is a relationship maintained; these are the people who might upgrade to bigger gifts, leave a legacy, or bring in new donors via word of mouth. So retention has compounding benefits.

Challenges

One challenge with AI-driven retention is ensuring outreach feels genuine and not “we noticed you haven’t donated, please do.” It must be value-driven (thanking them, showing impact, asking for feedback, inviting them to things) rather than just asking for money again. AI can flag when to do outreach, but the strategy on what to do should be thoughtful. Also, like all predictions, there will be false positives (contacting someone who wasn’t actually going to lapse) – one must ensure that doesn’t come off as odd. Typically, retention outreach is positive (thank-yous, etc.), so it rarely harms relationships, even if a donor wasn’t actually about to leave.

In summary, AI empowers charities to proactively care for their donors as individuals, catching signs of disinterest early and intervening in meaningful ways. It’s automating the wisdom a good fundraiser has (like “I have a feeling John might drift away, let’s check in with him”), but at scale for thousands of donors, which is humanly impossible to track without AI. By keeping more donors on board and happy, charities can steadily grow their funding base year after year, rather than spinning their wheels replacing donors who leave. This is a key aspect of accelerating fundraising: it’s not just about faster growth, but also about slowing the churn so that growth compounds.

9. AI in Charity Retail and E-Commerce

Many charities augment their donations by selling products – from branded merchandise to second-hand goods in thrift shops (charity shops), as well as running online stores or auctions (eBay for Charity, etc.). The income from these retail activities can be substantial (for example, the British Heart Foundation has one of the largest charity retail operations, funding research from shop sales). 

With the pandemic accelerating online shopping, charities have been expanding e-commerce. AI technologies that revolutionised online retail for businesses can similarly boost the profitability of charity retail by improving pricing, inventory management, and customer experience.

AI-Powered Pricing and Inventory for Second-Hand Goods

One challenge charity shops face is pricing donated items optimally. Price too low and you miss out on funds; price too high and the item might not sell. Traditionally, pricing relies on staff experience or manual lookup of item values (which is tough given the eclectic range of donations). AI tools like Listing Monster (a UK-based solution) have stepped in to assist. Listing Monster’s “Sourcing Monster” tool uses AI to value donated items: staff can snap a photo of an item, and the AI analyses similar items sold online to suggest a price and the best marketplace or channel to sell it. 

For example, say a charity shop gets a rare collectable plate. The AI might recognise it and suggest listing it on eBay with a starting bid of £100, based on recently sold listings data, whereas a volunteer might have priced it at £10, not knowing its value. This ensures charities maximise revenue from high-value donations instead of accidentally underselling them. It also works the other way: common items that won’t fetch much can be priced to move or directed to bulk outlets.

Additionally, AI can automate the listing process: generating keyword-optimised titles and descriptions for online listings, choosing the right format (auction vs buy-it-now), and even editing photos (removing backgrounds, etc., to meet e-commerce standards). Listing Monster claims that with their AI, a donated item can be photographed and listed online in under a minute, whereas doing this manually might take 5-10 minutes per item. For charities dealing with hundreds of donations daily, that’s a game changer in efficiency.

Dynamic Online Store Management 

For charities that have their own online shops (selling new goods like gifts, cards, event tickets, or donated items via a website), AI can help manage inventory and recommend products. Just as Amazon shows “related items” or “customers also bought,” a charity site can use AI to suggest additional merchandise or donation opportunities. For instance, if someone buys a charity t-shirt, the site could suggest, “You might also like our charity mug or consider a £5 donation to plant a tree.” AI can base these suggestions on what combinations have historically led to more revenue.

Customer Behaviour Monitoring 

As mentioned in the Oxfam example, they monitor online customer behaviours and preferences and are very interested in AI to enhance their shop. AI can crunch the web analytics to identify trends – e.g., noticing that Monday lunchtime is a peak shopping time (which it did, surprisingly), or that certain items sell better in certain seasons. The charity can then schedule promotions or list new stock to align with those patterns (like listing more items before the known busy time). AI might also detect if certain categories (vintage clothing, books, etc.) are performing well and recommend expanding those offerings.

Warehouse and Logistics Optimisation

For larger operations, AI can optimise how donations flow from collection to sale. For example, determining which items should go to the online shop vs physical store: Listing Monster allows setting rules (like “If estimated value > £50, list online; else send to local shop”). This ensures valuable items get national/global exposure online, while lower-value ones populate local shops where they can still sell to walk-ins. AI can also help manage stock levels and redistribution – if one shop has a surplus of something and another is lacking, AI could flag that.

Personalisation for Shoppers 

If a supporter logs into a charity’s e-commerce site, AI could personalise their experience (similar to donor personalisation but here as a customer). For example, if someone frequently buys second-hand books from the charity, the site could show them new book arrivals first. Or if another customer always buys the annual charity Christmas cards, AI ensures they see those as soon as they’re available each year.

Chatbots for Shop Support 

Customer service for online shoppers can also be aided by AI chatbots (similar to donor chatbots). Common queries like “Where is my order?” or “What is your return policy?” can be answered instantly by a bot, saving staff time and improving buyer experience.

Revenue Impact

AI in e-commerce helps in two main ways: increasing sales revenue and reducing costs. Higher accuracy in pricing means you don’t leave money on the table. Faster listing and centralised management mean you can sell more volume (the bottleneck is often how many items can be processed for sale). 

One interesting metric: how many items a shop lists per day and how many sell – if AI automation doubles listing output, you likely increase sales accordingly. Also, dynamic pricing can be employed – if something isn’t selling, AI can markdown the price over time (just like retailers do end-of-season sales) automatically, to ensure it eventually sells rather than never moving. Conversely, if something is hot, AI might suggest raising the price or using a bidding format. This agility can noticeably lift total revenue.

For cost savings, reducing manual work in listing and inventory means staff/volunteers can be allocated to other tasks, or a small team can manage a big operation. It also reduces training time – a volunteer might not know how to price antiques, but with AI guidance, they can handle it.

Innovation in Charity Retail

The Charity Retail Association and others have been encouraging members to embrace e-commerce and digital tools. We’re seeing an evolution: charity shops are no longer just brick-and-mortar; they’re becoming omni-channel retailers. AI is a key part of making that transition effective. Big charities are already on board (as Oxfam’s Head of eCommerce noted, AI is a major interest). But even smaller charities can use platforms like eBay for Charity combined with AI tools to punch above their weight in reaching buyers globally.

Example

Suppose a local hospice shop gets a donation of a high-end handbag. Instead of selling it in-store to the small local market, they use AI to identify it as valuable (maybe £200) and list it online with professional-looking photos and description. It sells to a buyer in another city for full value. That’s £200 to the hospice instead of maybe £20 if sold locally (where fewer recognise its worth). Multiply such instances over a year, and the difference in funds raised is huge.

In summary, AI brings the power of data-driven retail to the charity sector, allowing even volunteer-run shops to leverage sophisticated pricing algorithms and e-commerce strategies that were once only in the realm of big for-profit retailers. By doing so, charities can maximise income from their retail efforts, turning what might have been considered ancillary fundraising streams into significant contributors. 

With charity retail being a public-facing activity, the efficiency gains from AI also mean better donor/supporter satisfaction – supporters find what they want, feel their purchases have more impact, and see the charity as forward-thinking. All of this feeds back into a stronger brand and potentially more donors, too. So, AI in charity e-commerce accelerates fundraising both directly (through sales) and indirectly (through enhanced supporter engagement and perception).

10. Role of AI in Cryptocurrency Fundraising

AI Panes into the Crypto-Donation Landscape

Cryptocurrency fundraising or crypto philanthropy has surged in recent years. In 2024 alone, crypto donations to charities globally surpassed $1 billion, with over 70% of the top 100 U.S. charities now accepting digital asset gifts (Bitcoin, Ethereum, stablecoins, etc.) through platforms like The Giving Block, Endaoment, and Every.org. These platforms simplify the process by handling compliance, conversion to fiat, receipts, and donor support automation.

But where does AI come in? 

AI is beginning to shape crypto philanthropy in two powerful ways:

AI-Assisted Crypto Donor Engagement & Processing

JustGiving recently introduced cryptocurrency donations alongside a built-in AI assistant that helps fundraisers write compelling campaign stories, blending AI content creation directly into crypto-enabled fundraising pages.

On another level, AI can analyse large-scale crypto-giving patterns, optimising how and when to promote this giving method, and segment crypto-savvy donor bases for tailored outreach. Platforms can then recommend tax-smart timing, auto-generate compliance-ready receipts, or flag anomalous transactions, ensuring speed, transparency, and safety.

Charities Already Accepting Crypto and AI-Enhanced Processing

• Alzheimer’s Research UK accepts donations in over 100 types of cryptocurrencies via The Giving Block, offering automated tax receipts and seamless blockchain processing.
  
• ELHAP, a UK charity supporting disabled children, also accepts Bitcoin, Ethereum, and more via The Giving Block, converting crypto to cash efficiently.
  
• Community Foundation (Tyne & Wear/Northumberland) leverages the platform for secure crypto gifts, credited weekly when thresholds are met.
  
• Roald Dahl’s Marvellous Children’s Charity accepts a wide range of crypto donations and even explores NFT and DAO partnerships.
  
• National Zakat Foundation UK is accepting cryptocurrency donations via BitPay.
  

These charities benefit from AI-enhanced dashboards, donor analytics, and automated gift management embedded in crypto platforms, but the underlying AI capabilities are set to expand rapidly.

Benefits of AI in Crypto Fundraising

• Faster & smoother donation flow: AI-guided forms, smart receipt generation, and real-time compliance checks reduce friction.
  
• Enhanced donor personalisation: Analysing blockchain giving behaviour can tailor follow-up and stewardship—e.g., messaging crypto donors in digital asset terms.
  
• Tax-smart advice: AI could recommend optimal donation timing or structure (e.g., using stablecoins or DAFs) to maximise tax benefits, valuable for crypto-savvy beneficiaries.
  
• Operational scaling: AI streamlines crypto integration so even smaller charities can benefit, not just those with big tech teams.

Challenges & Considerations

• Volatility risk: Crypto values can swing significantly; some charities convert immediately, while others may expose themselves.
  
• Regulatory and tax complexity: Compliance differs by jurisdiction. Donors giving large amounts (e.g., £10,000+) may face vetting steps or need appraisals.
  
• Trust and transparency: Crypto philanthropy gains trust when AI helps with donation tracking and impact reporting, for example, via blockchain traceability.
  
• Barriers to access: Not all donors are comfortable with crypto. Education and seamless AI-assisted UX are crucial to broad adoption.
  

Future AI-Crypto Innovations to Watch

• AI-led autonomous crypto donations: The world’s first AI-led crypto donation in 2024 inaugurates a new era where AI systems could autonomously manage giving strategies and distributions.
  
• Smart contracts for conditional giving: AI could integrate with blockchain smart contracts to automate disbursement upon impact milestones, enhancing donor trust and transparency.
  
• AI-powered NFT fundraising: AI can assist in designing, minting, and marketing NFTs for charity auctions, balancing donor appeal and ethical marketing

In summary, AI is starting to transform cryptocurrency fundraising from a niche, complicated tech edge to a scalable, intuitive fundraising channel. By streamlining crypto gift processing, enhancing donor engagement, and paving the way for next-gen smart giving, AI is amplifying the impact of crypto philanthropy, helping charities diversify income, enhance transparency, and attract a new, digitally native donor base.

Bonus. Emerging AI Innovations for Future Fundraising

Thus far, we’ve covered current, practical applications of AI in fundraising. Finally, it’s worth looking at emerging AI-driven technologies that are on the horizon. Charities that start thinking about these now could pioneer new fundraising methods and be ready to capitalise as the tech matures. Here are a few future-facing ideas:

1 – Voice-Activated Giving and AI Voice Assistants

With the proliferation of smart speakers and voice assistants (Amazon Alexa, Google Assistant, Siri), voice-based donations could become a seamless experience. Already, Amazon’s Alexa supports charitable donations in some countries. The AI’s natural language understanding allows a donor to simply say, “Alexa, donate £20 to Cancer Research UK,” and it can authenticate and process that donation. As trust in voice transactions grows, charities might invest in creating voice apps or “skills” that engage supporters. 

For example, an AI voice assistant could walk a user through a guided story about a cause and ask if they’d like to contribute at the end. Islamic charities could leverage this in Ramadan – imagine an Alexa skill for Zakat calculation and donation, where the AI handles the calculations (which can be complex) and then facilitates the payment. This is still emerging, but the convenience factor is huge – no forms, no clicks, just speaking. Charities should ensure they’re discoverable on these platforms and maybe partner with tech companies to enable voice giving, as the user base of these devices is large and often includes demographics who might not visit websites but do use voice tech.

2 – AI-Enhanced Virtual Events and Metaverse Fundraising 

Virtual and augmented reality (VR/AR) present opportunities for immersive fundraising events. AI can animate virtual avatars, create responsive virtual environments, or even simulate beneficiary interactions. For instance, a charity could host a virtual reality gala where attendees’ avatars mingle in a digital venue; an AI might serve as the emcee or virtual guide, personalising the experience for each guest (“Hello John, welcome back! Check out the virtual exhibit of our project in Kenya.”). 

In the “metaverse” context (shared 3D virtual spaces), charities might build virtual mission sites where donors can “walk through” a village their money could help, with AI NPCs (non-player characters) telling them stories on the way. These experiences could drive emotional engagement and attract a younger, tech-savvy donor segment. While mass adoption of VR for fundraising isn’t here yet, some charities have experimented with simpler versions (360-degree videos, etc.), and adding AI will make those experiences interactive rather than passive.

3 – AI-Generated Videos and Deepfake Personalisation 

We’ve seen how AI can generate text; it’s also getting better at generating media. One future idea is personalised donor thank-you videos, where an AI could create a video of, say, a beneficiary or a celebrity ambassador addressing the donor by name. There was an experiment by a charity using AI to test if AI-generated images drive donations. Looking ahead, a charity could use a “deepfake” style AI (with ethical considerations and permission) to have, for example, an AI model of their founder or spokesperson thank each donor personally in a video, without recording thousands of individual videos. This could create a highly personalised touch at scale. 

Similarly, AI might produce custom impact visualisations – if a donor gave $X, an AI video might show “Because of you, 5 wells were built” with some animated infographic or map, tailored to that donor’s contribution. This level of personalisation in visual storytelling could dramatically increase donor satisfaction and loyalty. It’s futuristic but not far-fetched given the current trajectory of AI in video and image synthesis.

4 – ChatGPT-powered Donor Advisory and Education 

As AI gets integrated into more platforms, donors might start using AI themselves to decide how to give. For example, a donor could ask an AI (like a future ChatGPT with browsing), “What charity can make the best use of £1000 for education in Africa?” and the AI might draw from impact data and charity ratings to give suggestions. Charities will need to ensure their data and results are online and AI-accessible so that they are recommended in such scenarios. We might see AI-driven philanthropic advisory services that match donor preferences with charities, which could become a new channel for fundraising (akin to SEO for search engines; charities might optimise for AI advisors).

5 – AI and Blockchain for Transparent Giving 

Combining AI with blockchain (for transparency and smart contracts) could create “intelligent donations.” For example, a donor could give via a smart contract that only releases funds when certain conditions are met (verifiable by AI analysing data). Or AI could track a specific donation through the blockchain and report back to the donor exactly how it was spent, increasing trust. Some projects already explore tokenising charitable impact, and AI could help quantify and validate that impact.

6 – Predictive Analytics 2.0 (Macro level) 

We discussed micro-level predictions for donors, but future AI might predict macro fundraising trends. For instance, using economic data, social media sentiment, and giving patterns, AI might forecast a dip in donations next quarter and suggest contingency plans (like ramp up in one area to offset). It might also identify emerging philanthropic opportunities (e.g., a sudden surge of interest in funding climate action due to a news event, which a charity could capitalise on with a quick campaign).

7 – Enhanced Donor Experience through AI Concierge 

Imagine each major donor having an AI “concierge” available on the charity’s website or app – it knows everything about the charity’s work and about the donor’s interactions (to the extent data is shared ethically). The donor could ask in natural language any question (“How is project X going? When can I visit the site I funded?”) and the AI gives a rich, informed answer. It could even proactively send them updates it knows they’d care about. This kind of high-touch stewardship, enabled by AI, could improve relationships, especially with major donors or grantmakers.

8 – AI-Powered Partnerships with Fintech and Cause-Specific Apps

Another emerging trend is the rise of AI-enabled fintech apps that intersect with charity fundraising. These apps leverage AI to make giving easier, smarter, and more aligned with personal financial behaviour. For Muslim charities in particular, the opportunity is especially strong in Zakat, a mandatory annual obligation for Muslims to donate a portion of their wealth.

• AI for Zakat Calculation & Compliance: Calculating Zakat can be complex (assets, savings, investments, debts). AI-driven Islamic fintech apps such as Wahed Invest (wahed.com) and Zoya (zoya.finance) already provide AI-based halal investment screening and Zakat calculation tools. Charities can partner with these platforms so that once a user calculates their Zakat, they can donate directly through the app to approved charities. This creates a seamless “calculate → give” journey.
  
• Automated Round-Up & Micro-Giving: Fintechs like MyTenNights (mytennights.com) already allow Muslims to automate donations during the last 10 nights of Ramadan. AI can enhance this further by predicting the optimal giving pattern based on a donor’s past behaviour and income cycles, nudging them to give when they are most financially able.
  
• AI-Driven Impact Tracking: Donors are increasingly seeking transparency. AI-enabled fintech apps can integrate with charities to provide real-time impact dashboards, showing where Zakat funds were distributed and the outcomes achieved. This transparency builds trust and encourages recurring giving.
  
• Cross-App Partnerships: Imagine a global Muslim fintech wallet or super-app (like STC Pay in Saudi Arabia or Careem Pay in the UAE) using AI to identify when users have surplus balances or seasonal giving obligations, and prompting them to donate Zakat or Sadaqah to vetted charities instantly.
  

Benefit for Charities

By embedding themselves into everyday fintech apps that Muslims already use for financial management, charities can tap into the obligatory Zakat market (estimated at over $600 billion annually worldwide) with minimal donor friction. Instead of waiting for donors to come to them, AI + fintech brings the donation opportunity right into donors’ financial lives.

Challenges 

Ensuring compliance with Shariah standards, building trust with donors who want to know their Zakat is distributed correctly, and integrating seamlessly with financial regulators. Partnerships need to be transparent, with AI providing clear calculation logic and automated reporting to both donors and regulators.

Outlook 

This model of AI-powered fintech partnerships could become the standard for Zakat collection globally. Islamic charities that position themselves early with fintech partners stand to significantly increase annual Zakat inflows, especially among younger, digital-first Muslims.

Many of these future concepts align with opportunities identified in the SWOT analysis: they are new channels and methods to engage supporters. Charities, especially innovation-oriented ones, are already dabbling in some of these. Islamic charities might, for instance, be quick to adopt voice tech for Zakat (given the specific calculation needs and the cultural acceptance of new tech among a global Muslim donor base that’s young and connected). UK charities might lead on regulatory-friendly innovations, like transparency via AI, since trust and compliance are big in the UK sector.

Preparing for the Future 

CEOs and fundraising directors should keep an eye on these trends and possibly allocate a small R&D budget or form innovation teams to experiment. Maybe host a virtual reality fundraiser trial, or run a pilot with Alexa donations, or partner with a tech firm on an AI media project. The risk of not thinking ahead is that the charity could be left behind as donor expectations evolve with technology. Conversely, being an early mover can attract press, new supporters, and position the charity as a leader.

In summary, while core fundraising AI (like chatbots, analytics) is already delivering ROI, emerging technologies promise to further accelerate and transform fundraising in the coming years. By embracing things like voice giving, immersive experiences, and hyper-personalisation through AI, charities can create more engaging donor journeys than ever before. These innovations are about meeting donors where they are going – in their homes through smart devices, in virtual spaces, and in the personalised digital world – and making giving easy, relevant, and even delightful. Forward-thinking charities will start laying the groundwork now, as these future tools could well become standard practice in the next 5-10 years.

Conclusion

Artificial intelligence is no longer a sci-fi concept or a luxury reserved for tech giants – it is now an essential accelerator for fundraising in charities. From chatbots that handle donor queries instantly, to predictive analytics that forecast which campaigns will succeed, to hyper-personalised emails that triple response rates, AI is already reshaping how charities raise funds.

We’ve seen how AI:

• Engages donors 24/7 (chatbots, virtual assistants)
• Personalises outreach at scale (LLM-driven campaigns like Muslim Charity’s Ramadan appeal)
• Predicts donor behaviour (Parkinson’s UK netting £400k+ via predictive models)
• Optimises giving experiences (AI-enhanced donation platforms lifting online conversion rates)
• Supercharges communications (generative AI drafting content across emails, blogs, and social)
• Supports major grants and admin (AI drafting, automating, and reducing back-office costs)
• Improves retention (AI identifies at-risk donors before they lapse)
• Boosts charity retail (AI pricing and automating e-commerce operations)
• Explores new horizons (voice giving, virtual fundraising, immersive donor experiences)

And now, with the rise of crypto philanthropy, AI is helping charities accept and manage cryptocurrency donations more securely, transparently, and at scale. From platforms like The Giving Block enabling UK charities such as Alzheimer’s Research UK and Roald Dahl’s Marvellous Children’s Charity to accept Bitcoin and Ethereum, to AI-driven tax-smart processing and smart-contract giving, this fusion of AI and crypto offers charities access to a new, digitally native generation of donors and a fast-growing pool of alternative wealth.

For CEOs and charity leaders, the message is clear: AI is not replacing the human touch in fundraising – it’s amplifying it. By taking on the heavy lifting of admin, analysis, and personalisation, AI frees fundraisers to focus on what really matters: building relationships, telling authentic stories, and delivering impact.

The future of fundraising belongs to charities that are adaptive, ethical, and forward-thinking. Those who experiment with AI now – whether in donor engagement, crypto donations, or predictive campaigns- will position themselves as sector leaders, able to do more good with fewer resources.

AI is a catalyst for accelerating growth, diversifying income streams, and deepening supporter trust – ultimately unlocking more resources for mission delivery, faster than ever before.

References

• AI for Fundraising: How Nonprofits Can Use AI to Raise Money – Qlic IT
  https://www.qlicit.co.uk/ai-for-fundraising-how-nonprofits-can-use-ai-to-raise-money
  
• ‘Substantial growth’ in AI adoption as three-quarters of charities now use it – Civil Society News  https://www.civilsociety.co.uk/news/substantial-growth-in-ai-adoption-as-three-quarters-of-charities-now-use-it.html
  
• Muslim Charity – Ramadan 2024 AI Personalisation Campaign (Chartered Institute of Fundraising Awards)
  https://ciof.org.uk/events-and-training/resources/national-fundraising-awards-2024-shortlist#muslim-charity
  
• Muslim Charity Wins “Most Powerful Insight using AI/ML” Award – Muslim Charity https://muslimcharity.org.uk/news/muslim-charity-wins-most-powerful-insight-using-ai-ml-award
  
• Cutting Costs, Not Corners: AI’s Role in the Future of Fundraising – Medium (Lewis Gavin)
  https://lewisgavin.medium.com/cutting-costs-not-corners-ais-role-in-the-future-of-fundraising-9ef5b00a7e4c
  
• Five Examples of Charity Chatbots – Econsultancy
  https://econsultancy.com/five-examples-of-charity-chatbots
  
• 5 Ways to Drive Donor Engagement with AI for Nonprofits – Fundraise Up Blog
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• Donor Retention: Step-by-Step Guide to Retain More Support – Dataro Blog
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• Growing Online in the Charity Sector – Oxfam’s eCommerce (Interview on eCommerce Expo)
  https://www.ecommerceexpo.co.uk/content-hub-content/growing-online-in-the-charity-sector-oxfams-ecommerce
  
• Listing Monster AI – Solutions FAQ
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  https://www.charityexcellence.co.uk/Home/BlogDetail?Link=ChatGPT-for-Nonprofits-Discount
  
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  https://www.qlicit.co.uk/ai-and-fundraising-challenges-and-benefits
  
• Crypto Philanthropy – Wikipedia
  https://en.wikipedia.org/wiki/Crypto_philanthropy
  
• Give Crypto – Community Foundation Tyne & Wear and Northumberland
  https://www.communityfoundation.org.uk/give-crypto
  
• Blackbaud Enables Cryptocurrency Donations for U.S. Nonprofits through Its JustGiving Platform  https://www.blackbaud.com/newsroom/article/blackbaud-enables-cryptocurrency-donations-for-u-s-nonprofits-through-its-justgiving-platform
  
• Donate Crypto – Alzheimer’s Research UK
  https://www.alzheimersresearchuk.org/how-you-can-help/donate/donate-crypto
  
• Donate in Crypto – ELHAP
  https://www.elhap.org.uk/crypto-donation
  
• Donate in Cryptocurrency – Roald Dahl’s Marvellous Children’s Charity
  https://www.roalddahlcharity.org/get-involved/donate-in-cryptocurrency
  
• Donate in Crypto – British Red Cross
  https://www.redcross.org.uk/get-involved/donate/ways-you-can-give/donate-in-crypto
  
• Donate Crypto – GiveWell
  https://www.givewell.org/about/donate/cryptocurrency
  
• Blockchain for Charity Fundraising: Behind the Buzzword – Charity Digital
  https://charitydigital.org.uk/topics/blockchain-for-charity-fundraising-behind-the-buzzword-5882
  
• The Bitcoin Rally Has Driven Up Crypto Donations: How to Use Them to Score a Tax Break – Investopedia
  https://www.investopedia.com/the-bitcoin-rally-has-driven-up-crypto-donations-how-to-use-them-to-score-a-tax-break-8756011
  
• The Giving Block – Official Site
  https://thegivingblock.com
  
• The Giving Block Annual Report
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• How AI Helped Kids’ Cancer Project Almost Double Regular Donations – The Australian
  https://www.theaustralian.com.au/business/technology/how-ai-helped-kids-cancer-project-almost-double-regular-donations/news-story/a4ee4e170690de7b21b836847663c66e
  
• AI and Blockchain for Transparent Giving – arXiv Preprint
  https://arxiv.org/abs/2311.03573
  
• AI-Powered NFT Fundraising – arXiv Preprint
  https://arxiv.org/abs/2401.12064
  
• Wahed Invest – Official Site
  https://wahed.com
  
• Zoya – Halal Investment & Zakat App
  https://zoya.finance
  
• MyTenNights – Automate Your Donations in the Last 10 Nights of Ramadan
  https://mytennights.com
  
• Cashback websites: Can you really get cash for free? – The Guardian
  https://www.theguardian.com/money/2011/jan/22/cashback-websites-cash-for-free
  
• Donate Crypto – The Giving Block (UK Charity Partners)
  https://thegivingblock.com/solutions/for-nonprofits
  
• Crypto Donations – Endaoment (Nonprofit DAO)
  https://endaoment.org
  
• Crypto Donations for Nonprofits – Every.org
  https://www.every.org/crypto
  
• STC Pay – Official Site (Saudi Fintech Wallet)
  https://www.stcpay.com.sa
  
• Careem Pay – Careem Super App Wallet
  https://www.careem.com/ae/en/careempay

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