Revolutionizing Fundraising Part II: 5 Nonprofit Sector AI Application Examples

We learned about the applications of Artificial Intelligence (AI) in fundraising in Revolutionizing Fundraising Part I: Six Ways AI is Transforming the Nonprofit Sector, but what are some real-time insights into how nonprofits use AI to boost donor engagement and drive lasting impact?

AI can create efficiencies, such as making existing processes uncomplicated and faster, reducing chances of errors, getting better data, and helping staff focus on more challenging issues. Here are some examples of nonprofits using AI to help them reach their goals more efficiently.

AI Applications

Natural Language Generation to Create Donor Narratives

Natural Language Generation (NLG) uses machine learning and natural language processing to create human-like texts based on given prompts. NLG can turn donor data, including donation amounts, dates, and impact metrics, into personalized and captivating stories that connect with donors. This technology allows organizations to share the transformative impact of each donation, engaging donors and maintaining a high level of personalization while saving time and resources.

Example: See examples and screenshots of ChatGPT’s use to generate thank-you emails, social media content, announcements, etc.
How to get started: Get a deeper understanding of large-language models (LLMs) with Coursera co-founder and AI expert Andrew Ng’s course series on building applications using LLMs.
Note: Some online tools may use your input as training data for their models. Avoid entering sensitive and confidential information. Since these models are built on text from websites on the internet, the generated language could be biased, non-inclusive, and offensive. Finally, these models and tools often make things up. Always verify the generated text for accuracy and propriety.

Natural Language Processing to Analyze Sentiment

The Natural Language Processing (NLP) toolkit includes tools and techniques to analyze the sentiment of a text, categorizing it as positive, negative, or neutral. These tools can assess donor engagement or feelings about a nonprofit by studying donor emails or gift officer visit reports. In addition, nonprofits can build an organization-level dashboard to monitor their donor population’s sentiments.

Example: Amnesty International built Troll Patrol to detect online abuse using Twitter data.
How to get started: Review Hubspot’s list of sentiment analysis tools to experiment with.

Grateful Patient Data Technology to Reveal Opportunities

Healthcare fundraising often relies on the generosity of grateful patients and their families. However, identifying potential supporters among hundreds or thousands of visits and patients remains challenging. AI-enabled automation offers a new solution for nonprofits to connect with potential donors effectively. This technology automates data extraction and analysis, allowing organizations to identify patients who express gratitude for their care. Using the nonprofit’s criteria, the technology generates lists of qualified prospects based on wealth capacity, prospect information, and machine learning. This significantly reduces the time required for data gathering, analysis, and prospect identification.

Example: This research paper describes the prediction of patient experience using machine learning. Similar methods apply to any healthcare organization to predict patient satisfaction and turn positive experiences into qualified donor prospects.
How to get started: The CCS Data Analytics team can create a data management, augmentation, transformation, and dissemination solution for your organization. This solution will drastically reduce the time taken from data intake and clean-up to prospect recommendations. It will focus on ensuring that your institution uses this data successfully and strengthen a culture of philanthropy to raise transformational and sustainable support from patients.

Chatbots to Engage Website Visitors 24/7

Nonprofits use AI-powered chatbots on their websites to engage with visitors, answer questions, and facilitate donations. Such chatbots are trained on vast amounts of proprietary data and tailored with if-and-then rules. Chatbots can provide information to visitors and encourage them to donate to the cause. This helps reduce response time to common questions and helps direct donors to programs aligned with their giving priorities.

Example: World Wildlife Fund’s Facebook Messenger assistant
How to get started: Tools like Chatfuel will let you create a chatbot without complicated programming.

Image Recognition to Categorize Media Assets

AI-powered image recognition helps organizations catalog their media assets. The technology allows the nonprofit to easily search and retrieve images for use in fundraising campaigns and other outreach efforts, making the appeals more relevant and compelling while reducing staff time searching for images.

Example: National Geographic Society
How to get started: Amazon Rekognition allows you to automate image recognition.

The Power of AI to Maximize Resources

Nonprofits can benefit significantly from using AI, as seen in these examples. AI can help simplify work, reduce mistakes, gain valuable insights from data, and allow staff to focus on meaningful work. With AI, nonprofits can better engage donors, save time and money, and meet their goals. Taking the first steps to use AI can help nonprofits make strong connections, create lasting impact, and build a bright future for fundraising. Now the question is: What approach will you take to unlock the potential of AI within your organization?

Explore Part III of this Revolutionizing Fundraising series, which provides guiding questions to help your nonprofit decide whether and how to implement AI.