10 AI Best Practices For Nonprofits

We have written before on how AI will affect nonprofit organizations. But in this post? We get more specific about AI for nonprofits. Specifically, ten best practices your organization should remember when using the technology.

Implement this list, and you will be able to scale your impact more efficiently (and make better decisions overall).

Let’s check it out.

10 AI Best Practices For Nonprofits

1) Align AI With Mission Outcomes

AI is obviously a trending topic right now. But that’s not a good enough reason to adopt it at your organization. What to do instead? Start by identifying how exactly AI can help your organization achieve its core mission. 

Improving donor engagement? Enhancing delivery of your services? Identifying underserved communities? Connect AI to real-world outcomes that your team is striving for, and you avoid wasting your organization’s limited resources.

2) Prioritize Data Readiness

Using AI effectively requires extensive data. Unfortunately, not all of it is created equal. Your organization needs access to accurate and objective data. As for how you actually get that data? There are a few actions to take here for data readiness:

• Invest in better data collection practices
• Update any outdated systems that you use
• Train staff in how to maintain and use reliable data 

This is absolutely essential. Poor data isn’t just unreliable, but can actually result in harmful insights.

3) Start Small Before You Scale

As exciting as AI for nonprofits is, no use diving into complex tasks headfirst. This is what leads to overwhelm. Start with a manageable pilot project instead. This might include using AI tools to automate simple administrative tasks. Or maybe you want to improve donor segmentation. The key here is to start slow and learn from these experiences. The more comfortable you become with this technology, the more effectively your team will use them later on.

4) Invest in AI Literacy Across Your Organization

AI should be used by your entire organization. Not just your IT team. Even if a team member doesn’t use it every day, a basic understanding can go a long way. 

Consider team-wide training. Invest in cost-efficient education that will help your team level up their AI skills. When you foster this kind of culture of continual learning, the results compound over time. And that’s how AI pays you back over the long-term.

5) Incorporate AI Into Strategic Planning

Assuming you are going to invest in AI literacy, it’s time to make some long-term plans. Generally, AI shouldn’t just be a side project. It’s powerful enough to be integrated into your strategic planning. That’s why it’s helpful to reflect on where it fits in at your organization over the next few years. What will it help your team with? What resources will your organization devote to further implementing it? Answering these questions keeps AI aligned with your future growth.

6) Choose The Right Tools

There is increasingly a larger number of AI tools out there. The overwhelm is real. Where do you start, and which tools can you leave aside? Take a moment to think about your organization’s primary goals. Only when you get specific do you understand which tools are actually worth your time. When you have an answer – only focus on a few AI tools for nonprofits. That’s how you get really good at a few that make a difference, instead of constantly switching back and forth. 

7) Monitor For Bias

One of the biggest problem areas with AI for nonprofits? The technology unintentionally reflects or amplifies biases in your data. A software like ChatGPT will recite something to you with all the confidence in the world – and then turn out to be completely wrong in its conclusion.

This is why regular audits are so important. Human oversight is not only important, but necessary (especially if you’re using AI in areas that affect people’s lives or access to services). Monitor your results closely, and you are able to learn (and correct) faster.

8) Be Transparent With Stakeholders

Once you do start using AI at your nonprofit, your stakeholders need to know. This is the sort of practice that builds transparency and trust over time. It also ensures a certain level of accountability.

That said, no need to go overboard here; simply use plain language to explain how AI fits into your operations. The most important clarification here? Making clear which decisions are made by humans, vs. which ones are aided by AI tools. This honesty is refreshing in an era of “AI slop”. 

9) Measure And Revisit Impact Regularly

Just like we say with email automations, AI is not “set and forget.” Rather, it’s essential that you continuously evaluate its overall effectiveness. You can do this through both quantitative and qualitative metrics. Are you:

• Raising more funds? 
• Reaching more people?
• Improving your service outcomes? 

This information is essential in refining your approach and reporting results to funders and stakeholders. Remember: AI for nonprofits is not some kind of magic. Like anything else, it still requires your input. 

And our last tip about AI for nonprofits…

10) Use AI To Enhance Human Connection

Ultimately, a nonprofit is about the people. Even if your mission isn’t directly related to people, you are still working with them. This is why AI needs to be a way to improve human connection. Not replace it.

Use AI to free up staff time so they can focus on real interactions (conversations with donors or hands-on support for beneficiaries). AI for nonprofits is all about helping your team do their job better. And when you use it in the right way, you are able to scale your effectiveness as a result.

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