P2P Predictions: The Power of AI

In our Digital Fundraising Predictions for 2023 post, I said we should look for Artificial Intelligence (AI) to play an increasingly important role in helping nonprofits further their missions. In this post, I want to expand on that prediction that nonprofits will begin using AI for fundraising and provide some additional food for thought.

Machine learning and AI-powered tools have been around for a while. For instance, many nonprofits take advantage of Facebook’s automated optimization of ads that target donors. But as AI technology advances and becomes more accessible, nonprofits have an opportunity to harness the power of AI to do even more to increase fundraising revenue, improve efficiency, and gain deeper insights about their supporters.

In 2019, the AI in Advancement Advisory Council released a study that reported 89% of nonprofit professionals believed that AI can make their organization more efficient, but only 28% reported their organization had deployed, were implementing, or experimenting with AI. The tide seems to be turning. The past couple of years have seen the emergence of a number of turnkey solutions, as well as open APIs, that allow nonprofits to harness the power of AI for fundraising.

There are a number of ways in which nonprofit organizations can use AI and machine learning to further their missions and achieve their fundraising goals.

Here’s a look at a few of the leading use cases:

Data Analysis & Insights

Nonprofits can use AI to analyze and make sense of large data sets, which can help them identify trends, patterns, and insights that can inform decision-making and strategy. One area where this may be particularly useful is in cultivating donors. Hatch.ai and Dataro.io are two companies that offer machine learning algorithms paired with predictive and propensity models to provide profiles of donors who are likely to take a particular action. Through tools like these, organizations can boost their fundraising results, using artificial intelligence to streamline the segmentation process.

Predictive Modeling

AI has the potential to build predictive models that can forecast future outcomes or identify potential areas of risk or opportunity. This can be particularly useful for organizations working in areas such as public health, where the ability to predict and prevent negative outcomes can be crucial.

Personalization

Nonprofit organizations have a great asset in their data. Machine learning and data analytics algorithms can extract valuable insights and inform better, more personalized communication with donors through messages that are tailored to specific individuals or groups based on their interests, needs and preferences. Boodle.ai is one platform that uses AI-powered insights into donor traits like giving capacity and communication preferences to help nonprofits deliver more targeted messaging.

Automation & Efficiency

Nonprofits should consider using AI to automate certain tasks and processes, freeing up staff time and resources to focus on higher-value activities. This can include using chatbots to answer frequently asked questions or route constituent queries to the appropriate internal resource for a more detailed response. Open.ai has several natural language processing chat tools that developers can utilize through an API. Off-the-shelf chatbot solutions also exist for organizations that may want to start small and test before committing developer resources.

Impact Measurement

Nonprofits may want to consider using AI to track and measure the impact of their work, using data and analytics to understand the results and outcomes of their efforts. Using AI for fundraising in this way can help organizations better understand the effectiveness of their programs and identify areas for improvement.

According to the McKinsey Global Survey on AI, adoption of AI by businesses has more than doubled over the last five years. Given that for-profit businesses have proven that AI can increase revenues and reduce costs, it only makes sense that nonprofit organizations will follow suit and increase their adoption of AI technologies as well.