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James Barnard 12 min read

5 AI Fundraising Ethical Considerations for Nonprofits

Despite its controversy, artificial intelligence (AI) is becoming increasingly popular in a variety of industries for streamlining internal processes, enhancing decision-making, and saving staff time. 

Introducing AI into your charitable or nonprofit organization's fundraising process can allow for greater efficiency and ultimately maximize your results. As BWF explains, AI fundraising use cases range from nonprofit content generation to predictive donor analytics to prospect identification.

However, there are some considerations your organization needs to take into account to ensure you’re using AI responsibly.

We’ll review the top five considerations to encourage ethical yet effective AI fundraising practices.
5 Ethical Fundraising considerations

1. Data Privacy and Security

It’s important to protect donor data so you keep their information secure and maintain their trust. When you introduce new tools such as AI into the fundraising process, you could open up the possibility of data breaches, meaning the loss of donors’ sensitive information, such as personal details and payment information.

Besides eroding donors’ trust, there are several other risks associated with data breaches or misuse:

  • Damage to your organization’s reputation. When sensitive donor data is leaked, those affected will be less likely to recommend supporting your nonprofit to family and friends. As a result, you could experience a hit to your organization’s reputation and find it harder to gather new support.
  • Legal and regulatory consequences. In some cases, organizations could face lawsuits or regulatory penalties for negligence in protecting donor data and failure to comply with relevant data protection laws.
  • Operational disruptions. When your nonprofit experiences a data breach, rectifying the issue quickly becomes your priority, causing you to neglect other fundraising activities and mission-critical work.

To avoid data breaches, collect, store, and process all data used in the AI fundraising process responsibly. Use a dedicated constituent relationship management system (CRM) with built-in cybersecurity measures to protect donor data from hackers and unauthorized users. Following data hygiene procedures such as auditing your database can also make it easier for you to quickly identify data breaches and immediately start working to remedy any security issues.

2. Bias and Fairness

Biases in data and training processes used for predictive analytics can lead to unfair targeting or exclusion in fundraising campaigns, creating a negative experience for your supporters. For example, biased data can lead to:

  • Selective targeting. When you train your AI algorithms using historical donation data that unevenly represents certain demographics, you may accidentally prioritize or exclude specific groups in your fundraising process.
  • Misaligned donation requests. If you make donor outreach decisions based on biased data, you may set ask amounts too high or too low for certain donors, damaging your relationships with those supporters.
  • Event invitation disparities. When using AI to create guest lists for fundraising events, your algorithm might unfairly select attendees based on biased criteria, such as past donation amounts or specific demographic factors. As a result, you might unintentionally host exclusive events that alienate a portion of your supporter base.

While it’s easy to inadvertently introduce bias into AI fundraising, it’s perhaps even easier to prevent and address these potential biases. Use these tips to mitigate bias and promote fairness in the AI fundraising process:

  • Use diverse data sets to train your AI algorithms.
  • Audit your algorithms to identify and correct any biases.
  • Test your AI systems across different scenarios and user groups.

When you remain vigilant and aware of potential AI fundraising biases, you ensure that your algorithms don’t favor any one particular group or cause friction with certain portions of your supporter base.

3. Transparency

Build and maintain donor confidence by being transparent about your organization’s AI use. Provide clear explanations of how your nonprofit uses AI to guide decision-making and improve the fundraising process.

If your nonprofit leverages AI responsibly, there should be no issue sharing how you’re using these tools to strengthen your fundraising efforts and increase support for your cause. Break down the ways you’re using AI to make it more understandable for stakeholders. For example, you may feature your AI policy on your website and email your supporters when your organization refreshes this policy.

With all the controversy surrounding AI, it can be a murky, off-putting topic for donors. Prove to them that when used according to best practices, AI is a useful tool, just like any other software or technology your organization already leverages.

4. Donor Autonomy

As 360MatchPro explains, “...the idea of AI has become particularly beneficial to nonprofit fundraising efforts thanks to the ability to automate donor engagements while maintaining a personal flair.” However, some may see using AI to optimize the fundraising process as manipulating donor information.

Make sure to differentiate between personalization that enhances the donor experience and tactics that leverage AI in a way that could be seen as manipulative. One surefire way to protect donor autonomy along the way is to obtain consent for collecting and analyzing data for personalized fundraising.

Consider sending donors an email that explains how you’ll use AI to improve their experience with your nonprofit. For example, by using donor data and AI, you can send donors emails for specific engagement opportunities they’re most likely to be interested in as opposed to just soliciting donations and sharing general email blasts.

Then, allow donors to control their preferences in this area, such as which types of communications they’d like to receive, the frequency of contact they’d like to maintain, and the option to opt out of data-driven personalization entirely. Overall, ensure you’re using AI to provide additional value to donors, not to manipulate their emotions or decisions by capitalizing on vulnerabilities or biases AI may detect.

5. Accountability

Holding your organization accountable for responsible AI fundraising allows you to mitigate friction with donors and ensure you’re using AI in a way that’s positive for everyone involved. Follow these tips to promote accountability surrounding your nonprofit’s AI use:

  • Develop clear AI internal policies and guidelines.
  • Be prepared to explain and take responsibility for AI-based decisions.
  • Ensure you have processes in place to address any donor concerns or adverse effects of AI.

With any new tool, mistakes are inevitable, but it’s the way you handle and rectify these issues that matters. Commit your organization to continuously improving its AI approach through conducting research, collecting feedback, and implementing refinements that will make the resulting donor experiences better and better.

Whether you’re using GPTs, data-driven algorithms, AI-powered chatbots, or another related tool, it’s up to your organization to use AI ethically and responsibly. Doing so will not only maximize positive outcomes from AI but also maintain donor trust so you can continue building strong relationships with your supporters and making a positive impact on your community.


James Barnard

James Barnard, Associate Managing Vice President of Annual Giving and Digital Marketing at BWF James an integral part of the team at the global fundraising consultancy BWF. He helps nonprofit clients develop digital strategies for fundraising and marketing. James has been active in CASE for a number of years, participating as a conference speaker and CASE District II board member.