4 Data Governance Rules for Ethical AI in Fundraising

Guest post by Heller Consulting

Within the nonprofit sector, AI’s capabilities can be a game-changer. AI has empowered nonprofits to cut down previously time-consuming tasks, from writing personalized emails for different donor segments to determining the ideal suggested gift amount.

The benefits of AI are significant, but nonprofits should proceed with caution. Like any new development, there are nuances that should inform your organization’s approach. Setting up smart, informed data governance for your nonprofit’s AI use will ensure that your approach is sustainable and safe for your employees, donors, and community. In this article, we’ll explore four pillars for ethical governance.

Why ethical AI data governance is important

As AI tools become more accessible to nonprofits, donor data processing has changed, too. Traditional data governance practices alone fall short when protecting your organization’s, donors’, and other stakeholders’ privacy.

When you implement strong governance policies, you ensure that your entire nonprofit is elevated by AI. A few of the advantages include: 

• Focus on organizational resilience: Proactive frameworks prevent costly breaches and ethical missteps before they occur, building a resilient infrastructure that can adapt to new technological advancements.

• Connecting technology to mission: Responsible technology use directly supports broader organizational goals and community trust, ensuring that innovation aligns with your institution's core values.

• Keeping pace with the industry: Standard spreadsheets and static databases are falling by the wayside in favor of algorithms that continuously process complex supporter engagement behaviors and their giving histories. Your nonprofit needs to stay on the cutting edge to remain competitive. 

Approaching tech integration through a governance-first lens transforms potential vulnerabilities into operational strengths. By securing your data pipeline early, your team can experiment with new tools confidently without risking your community's trust.

Data governance essentials for AI-powered fundraising

1. Prioritize stringent data protection

The foundation of any ethical technology strategy is an unwavering commitment to data security. Before implementing any predictive models or generative tools, your development, IT, and executive teams should collaborate to ensure existing infrastructure is protected against internal and external threats.

To build a secure environment for your constituent data, consider the following steps:

• Secure sensitive constituent information against unauthorized access. Implement role-based permissions and regularly audit your systems for weaknesses, such as poor access controls and misconfigurations, weak authentication, and data corruption. 

• Vet the security of third-party AI tools thoroughly to guarantee they meet high standards for encryption, data sovereignty, and compliance with regional privacy regulations. If your organization has a Shadow AI problem, you’ll need a strong policy.

• Collect only strictly necessary data from donors and other stakeholders. Heller Consulting’s data management guide states that “hoarded data is a liability.” By only storing necessary information in your database, you’re protecting your organization and donors from additional risk. 

Ask potential software vendors to provide a detailed overview of how their algorithms store and process your specific data inputs. If a vendor cannot clearly explain their data retention and model training policies, they pose an unnecessary risk to your institution.

2. Implement policies for consistent usage

Unfortunately, user error is just as much of a risk as unvetted technology. Improper (or even inconsistent) technology use can undermine the most secure software protections. To set boundaries for acceptable data use and handling, your nonprofit should establish a unified approach. 

Much of your team likely uses AI already. Your nonprofit needs a standardized set of data procedures across the board, no matter what role or AI use case a staff member is using.

As you develop standards across the board for your nonprofit’s use of AI, here are a few aspects to include in your AI use policy:

• Clearly defined acceptable and unacceptable uses of AI

• Approved AI tools that your organization uses

• Best practices for data handling and management

• Training for your team to understand how AI works and its primary use cases

Once these standards are in place, require all staff members to pass an annual AI training or attend an AI workshop. AI is rapidly evolving, so remember to review and update any training content and policies quarterly. To support your team through these changes, assign a dedicated staff member or a committee to monitor these updates and make the necessary changes. 

3. Ensure transparency with stakeholders

Since fundraising is so relational, the trust you’ve built with your donors is one of your most valuable assets. Some members of your community may mistrust AI systems, so you need to openly communicate your intentions and AI use policies with donors.  When they understand how you’re using AI tools to support your mission and the measures your team has implemented for safety, donors are more likely to be on board. 

To foster transparency and respect donor preferences, prioritize:

• Open communication. Publish your AI use policies clearly on your website and provide community members with your contact information so they can reach out for clarification if needed. 

• Community empowerment. Provide clear opt-out mechanisms and accessible privacy notices to respect donor and community members’ autonomy.

Consider dedicating a section in your annual report to explaining how new technologies have improved your operational efficiency. Framing data use as a stewardship and cultivation tool helps donors see the direct connection between their data and your community impact.

4. Mandate human review in automated processes

For any digital transformation projects your nonprofit engages in, it’s important to take a human-centered approach. Automation drastically reduces administrative workloads, but it shouldn’t replace your development team’s empathy and nuance. 

Maintaining a human-in-the-loop approach protects your organization by:

• Preventing algorithmic bias or errors: Maintain human review over AI-generated insights and content to catch algorithmic biases or factual inaccuracies before they reach the public.

• Retaining empathy in outreach: While technology can optimize targeting and segmentation, the human touch ensures communications remain authentic, empathetic, and perfectly aligned with institutional values.

Use generative tools to draft the initial framework of a major donor appeal or grant proposal, but require a development officer to finalize the narrative. Ultimately, a human editor can catch AI mistakes, tonal inconsistencies, and context gaps that an algorithm cannot.

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Adopting AI requires a commitment to responsible data management to truly benefit your institution. By treating data governance as an ongoing operational priority rather than a one-time IT project, your organization will be positioned to scale its impact securely.

Exploring the Benefits and Challenges of AI for Nonprofits

Guest post by DonorSearch

It’s no secret that tools powered by artificial intelligence (AI) have increasingly become part of daily life, from online chatbots to social media algorithms and even facial recognition. Similarly, AI use has become a trend in the nonprofit sector as organizations are discovering that machine learning and intelligent content generation can enhance many aspects of their management and fundraising efficiency.

While many of the available AI tools for nonprofits can benefit your organization, there are also real risks associated with using them improperly. If you’ve experienced pushback from leadership about implementing AI at your nonprofit, you aren’t alone!

However, if your team uses AI responsibly, its benefits significantly outweigh the risks. In this guide, we’ll discuss some of the advantages of AI for nonprofits before diving into some common challenges with these tools and ways to overcome them. 

Benefits of Leveraging AI at Your Nonprofit

Although AI tools can be used in many aspects of your nonprofit’s work, they tend to provide the most advantages when it comes to fundraising. DonorSearch’s AI fundraising guide lists seven general roles that AI plays in engaging donors and generating revenue for nonprofits’ missions, including that it: 

1. Saves time and money by allowing you to work smarter, not harder, on more targeted efforts.

2. Automates mundane tasks so you can focus on decision-making, relationship-building, and other activities that require human oversight.

3. Personalizes the supporter experience through segmented outreach, consistent follow-ups, and tailored fundraising appeals.

4. Provides accurate and actionable insights via detailed analytics and recommendations to maximize fundraising effectiveness, especially when it comes to identifying and cultivating major donors.

5. Levels up your marketing efforts by generating higher-quality content that resonates with your target audiences.

6. Taps into exciting new donation methods while also optimizing your existing campaigns to maximize donor engagement.

7. Measures your organization’s impact so you can identify strengths and areas for improvement in your fundraising strategy.

Of course, you can also leverage AI in other areas of your nonprofit’s work outside of fundraising—for example, generating content to promote your programs to beneficiaries or modeling financial data to inform the creation of your annual budget. Think of your AI tools as collaborators in your organization’s mission-driven success since using the best solutions in the most effective ways will provide you with new capabilities that increase your capacity to make a positive impact on your community.

Common Nonprofit AI Challenges (& How to Overcome Them)

As mentioned above, the risks of improper AI use are very real—they include data breaches, biased decision-making, noncompliance with legal regulations, and more. However, your nonprofit can prevent these risks while maximizing the benefits in the previous section by making a commitment to leverage AI responsibly.

Let’s dive deeper into a few of the challenges that many nonprofits face when implementing AI and how your organization can overcome each one.

Ensuring Data Privacy & Security

AI tools process and analyze copious amounts of data—some of which includes sensitive information about your nonprofit’s existing supporters, prospective donors, and beneficiaries. It isn’t surprising, then, that concerns about data protection with these solutions may arise both inside and outside your organization.

Fortunately, your nonprofit can keep community members’ personal information safe by taking similar precautions with your AI tools that you would with other software. As a start, Double the Donation’s donor data guide recommends taking the following security steps:

• Implement access controls. Ensure only team members who need to use AI-processed data for their jobs can work directly with it. Each of them should have their own login credentials with strong passwords that are updated regularly.

• Use reliable solutions. Look for AI tools with security features built in, such as encryption and multi-factor authentication. Some providers have also committed to promoting responsible AI use in the nonprofit sector (such as members of the Fundraising.AI Collaborative), so do your research before choosing solutions for your organization.

• Regularly update and patch systems. AI is constantly evolving and learning from new data, and new security measures are often rolled out as this happens, too. Ensure you’re always using the most up-to-date version of your solutions to maximize data protection.

Once you’ve implemented these measures, focus on being transparent with your nonprofit’s supporters about how you’re using their data for AI fundraising and allowing them to opt out if they wish to do so.

Preventing Unintentional Bias & Discrimination

Before they can produce useful outputs, AI tools must be “trained” to recognize patterns and draw conclusions from existing data. However, sometimes solutions are trained on biased data, or the algorithms they’re based on were designed (intentionally or unintentionally) in a way that perpetuates harmful biases and leads to discrimination.

To mitigate this problem, ensure your nonprofit’s responsible AI commitment includes the principle of inclusiveness. Monitor and evaluate your systems’ outputs to verify that the information is representative of your organization’s community, promotes equality, and allows you to make objective, fair decisions based on it.

Additionally, there are steps you can take to promote inclusiveness through your use of AI tools. For instance, if you use AI image generation tools, prompt them to create outputs that feature diversity. Or, if you create audio and video content with AI, ensure the solution generates a transcript and closed captions to make the finished product accessible to all audience members. Maintaining diverse and accurate data in your organization’s databases also gives your AI tools a more inclusive source of information to pull from in analysis and modeling.

Maintaining a Human Touch

AI is meant to assist your nonprofit’s team with content creation and data-driven decision-making. Organizations often run into problems when they let AI do the work for them.

Your fundraising efforts will be most effective when they’re human-centered, even if AI also supports them. Use your content generation tools’ outputs as a starting point for donor communications, but edit the outputs to tailor them to your organization and audience before sending them off. Before you make any decisions based on machine learning models, discuss the results with your team and ensure they align with your nonprofit’s overall strategy.

Additionally, remember that as advanced as AI technology is, building genuine relationships with supporters is still a human activity. While AI can save time on data-gathering and preparation for donor interactions, it’s still up to your staff members to get to know each donor personally and use your understanding of their needs and preferences to inform their journey with your nonprofit.

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AI is the future of nonprofit work, especially fundraising. By committing to responsible AI use and investing in the right tools now, your organization will be well on its way to more effective decision-making, outreach, cultivation, and retention for the long term.