Artificial Intelligence is a broad field with a wide range of sub-fields, and data science also sometimes uses AI. Almost every application of AI depends on the input data, which the AI algorithms use to predict an output. One preferred definition of AI is “Prediction Machines,” given in the namesake book by Ajay Agarwal.
With the power of AI, nonprofit organizations can now automate and optimize their fundraising practices to engage donors more effectively and make a more significant societal impact.
Consider these six applications of AI in fundraising.
1. Giving Likelihood Prediction
One of the most promising applications of AI in fundraising is giving likelihood prediction. By studying the donation history of donors in a dataset, AI algorithms can predict the likelihood of future donations. These predictions can then be used to group donors, such as lead annual giving or major donors, and tailor communication and fundraising strategies accordingly. A popular technique for such predictions is Random Forests, more commonly referenced as “decision trees,” graphical representations of all the possible solutions to a decision based on certain conditions. AI takes the manual decision-making process out of the mix and does it for you.
AI can segment prospects or donors based on similarities such as geography, age, donation history and preferences, major in college, graduation year, and other factors. This can help to customize fundraising strategies to better engage and retain donors. Clustering or cluster analysis is a commonly used method to create these segments. Giving likelihood models can be combined with segmentation to help with donor retention or upgrades.
3. Text or Language Generation
AI language generation models such as ChatGPT and the underlying generative pre-trained transformer (GPT) models have gained attention for their ability to generate text and language. In the context of fundraising, language generation models can be used to generate qualification emails, thank you or stewardship letters, proposal generation, and research profile creation.
4. Image, Video, Music, or X Generation
AI can generate images, videos, music, or other forms of content. These models are trained on large datasets of images or other media using a combination of human labeling and computerized description. Some fundraising applications are graphic generators for communications, personalized stewardship videos, or dynamic proposals.
5. Augmented or Virtual Reality (AR/VR)
Augmented and virtual reality (AR/VR) can also be used in fundraising to transport prospective donors into an imaginary world to show the impact of their gifts. While not strictly in the AI domain, AR/VR technology can overlay different objects into our physical world or transport us to a different one.
6. Data Science
Data science is an applied field that can be used to stitch together unique fundraising solutions by analyzing large datasets to identify trends, insights, and opportunities for optimization. AI technologies can automate and optimize various fundraising practices and operations, enabling nonprofits to focus on their core mission of positively impacting society.
In conclusion, AI can revolutionize the fundraising sector through its ability to provide valuable information on donor behavior, segmentation, communication, and content creation. Nonprofits can use AI technologies to automate and enhance their fundraising practices and operations, allowing them to take the guesswork out of what may yield the most remarkable results and concentrate on their primary objective of creating a more significant impact on the world.
Part II of this Revolutionizing Fundraising series will explore real-time examples of this work and how you can apply AI techniques to your fundraising plan and outcomes. Stay tuned!
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