4 Considerations for Nonprofits Planning to Embrace AI

I participated in a series of AI strategy sessions with clients toward the end of 2023, and one thing rang true throughout my conversations: both non- and for-profit organizations across all sectors and industries are leaning into the power of AI but are often face challenges in fully implementing it. 

For nonprofits, these challenges may include operating with limited resources, maintaining alignment with their mission and values, and having the bandwidth to prioritize digital infrastructure investments when funds are limited.

In addition, nonprofit stakeholders — be it employees, donors, or volunteers — are raising concerns about the use of AI at the organizations they work with, including proactive concerns before organizations are even deploying AI. This is an additional hurdle that nonprofits will have to navigate before — and likely during — the introduction of any AI initiatives.

There are many benefits for nonprofits to begin integrating AI into their processes and procedures once any stakeholder concerns are alleviated. This includes (but is certainly not limited to):

• Volunteer coordination. AI tools can help nonprofits match volunteers with opportunities that are best suited for their interests, skills, and past participation. Using AI can automate this traditionally manual process, making it more efficient while also providing volunteers with an enhanced experience and increasing the impact of their contributions.
• Donor management. Nonprofits can use AI tools to identify trends and patterns in donor behavior. This can help anticipate future giving and contribute to more informed, targeted outreach strategies.
• Program development. Nonprofits can make their programs and initiatives more effective with predictive analytics tools that enable them to forecast outcomes, monitor real-time progress against these predicted outcomes, and adjust strategies accordingly. This helps enable more accurate long-term planning and resource allocation and can also help proactively identify potential risks and opportunities.
• Personalized communications: AI can assist nonprofits with their communications and outreach efforts to create tailored communications based on engagement levels and past interactions. This leads to messages that feel more personal to their recipients, which may increase their likelihood of future support.
  
  

A robust data foundation and a comprehensive AI strategy are crucial to overcoming these challenges and enabling nonprofits to embrace AI solutions. Here are some of the key takeaways from our AI strategy sessions that nonprofits may be valuable to nonprofit leaders looking to bring AI solutions to their organizations.

Build Familiarity with AI Tools

With heightened concerns around the uses of AI tools, it will be important for nonprofits to clearly articulate how these technologies align with (and support) their mission and strategic goals. In addition, to alleviate any internal hesitations about implementing new tools, it will be helpful to understand where AI solutions may already unknowingly be in use. While the popularity of generative AI is still relatively recent, many of the tools that nonprofits are using day to day already have automation and AI features built in — and may have for quite some time. Identifying these uses and highlighting how they are already in place may help to make employees more comfortable with larger AI initiatives. 

Proactively Address Risks and Concerns

As with any new technology, there are going to be risks and concerns that should be identified and safeguarded before jumping in. Examples include — but are not limited to — bias and data security. AI can unintentionally perpetuate or amplify biases if diverse, representative data is not used, so be sure to conduct regular bias trainings and have a plan in place for detecting and minimizing biases when introducing a new AI solution to the organization. Data privacy is particularly important for nonprofits due to the sensitive information (donor demographics, beneficiary data) that is often stored. When implementing AI solutions, be sure that any updates to existing processes and procedures adhere to data privacy best practices, including storing and transmitting data safely and securely.

Map Out Your Approach

A successful AI implementation starts with a strategic roadmap that details your organization’s data and AI maturity goals, including potential pain points and any technical gaps that may need to be addressed. Once these core components are identified, the next step is to determine what is within the organization’s wheelhouse to implement. This may be achieved within the team’s existing skillset, or it could require some training and upskilling. Some organizations may also choose to work with an external advisor.

Build Your Use Cases

Once the foundation is in place, it is time to develop proof points of how AI can benefit your organization. As a first initiative, consider something that is easier to manage, has clear metrics and a strong ROI, and can easily lead to tangible success. Some ideas include a donor data analysis powered by predictive analytics, automating a volunteer management database, or using generative AI to generate content for donors. These uses can go a long way toward demonstrating how AI solutions can amplify your organization’s message, help you reach a wider audience, and free up staff to focus on more high-value work.

Being nimble and intentional at the onset of your organization’s foray into AI solutions can help you move from small use cases to larger-scale initiatives. By embracing these key themes, organizations can unlock the full potential of AI to pave the way for future growth and success.