Starting something new can often feel overwhelming, and for many nonprofit leaders, figuring out where to begin with AI is no different. Conversations about Artificial Intelligence seem to be everywhere—on the news, in advertisements, and from technology vendors promising revolutionary solutions from donor engagement to marketing automation. But where do the realities of Artificial Intelligence stand today for nonprofits, foundations and associations?
The AI Hype and the Gartner Hype Cycle
If you’ve felt like you’re being left behind as everyone talks about AI, you’re not alone. This sense of urgency reflects a phenomenon often captured by the Gartner Hype Cycle—a model that illustrates the adoption of emerging technologies, from the initial “Peak of Inflated Expectations” to the crash into the “Trough of Disillusionment” and eventual movement toward the “Plateau of Productivity.”
It’s been useful framing, for me, as I see the initial AI euphoria modulating and questions growing about AI’s value and practicality. The stakes for the nonprofit sector, with even greater constraints on investment, are incredibly high.
Right now, the buzz surrounding AI can feel overwhelming and, candidly, a bit justified. In a recent Wall Street Journal article, Early Adopters of Microsoft’s AI Bot Wonder if It’s Worth the Money, numerous leaders have expressed concerns regarding the current value of Microsoft’s CoPilot in relation to its cost. A Boston Consulting Group survey found that nearly 90% of business executives prioritized generative AI, but almost two-thirds believe it will take at least two years to go beyond the hype. Approximately 70% focused solely on small-scale, limited tests.
For nonprofits, this gap creates both challenges and opportunities. While there’s significant potential, nonprofits, foundations, and associations must approach AI adoption thoughtfully and with realistic expectations.
The Trough of Disillusionment for Nonprofits
Many early adopters of AI find themselves grappling with the realities of limited short-term payoffs. For nonprofits, challenges such as resource constraints, skepticism from board members, and unclear immediate ROI impede adoption or planning for the future. Questions about AI loom large.
At a recent Microsoft Nonprofit Global Summit, AI was center stage. Speakers addressed both AI’s potential benefits and its risks—the biases, the uncertainties, and even the challenge of navigating “AI hallucinations.” Inspired by these discussions, I saw immense potential for AI to transform areas such as donor engagement, service delivery, and access to critical services. Yet, as exciting as these ideas were, it has become clear that meaningful change requires patience and incremental progress. The Gartner Hype Cycle helps provide a meaningful framing for the nonprofit, foundation and association sectors.
Nonprofits looking to implement AI must prepare for the hurdles of the Trough of Disillusionment. Solutions today require time, expertise, and experimentation to become effective tools. Early adopters may grow frustrated when donor experiences or member engagement don’t instantly improve, but for organizations willing to stick with it, the downstream benefits could be transformational.
Preparing for the Plateau of Productivity
The good news? The period of disillusionment won’t last forever. The Gartner Hype Cycle points toward a future where we have a clear, grounded understanding of how AI can drive innovation and efficiency in the nonprofit sector.
I wrote a blog post, Nonprofit Artificial Intelligence: Unlock Its Power For Impact, which provides an action framework. It highlights that adopting Artificial Intelligence is a marathon, involving many small sprints. There are things that nonprofits, foundations, and associations can start with today that will get your organization on the “Slope of Enlightenment”.
1. Develop a Data Strategy
AI is only as effective as the data it works with. Start by organizing and cleaning your organization’s data. Whether it’s donor information, service outcomes, or event participation, building a strong data foundation is essential. A well-executed data strategy ensures that when Artificial Intelligence tools are introduced, they function as intended.
2. Run Small Artificial Intelligence Pilots
Rather than committing to large-scale AI implementations, focus on small, experimental pilots where measurable outcomes can be tracked. For example:
- Implement a chatbot to assist with basic inquiries.
- Use AI tools to analyze donor data for insights into engagement trends.
- Pilot AI applications in marketing campaigns to identify which messages resonate most with your audience.
By starting small, you’ll build internal capacity and gain a better understanding of what works for your organization.
3. Foster a Culture of Learning about Artificial Intelligence
AI adoption is a marathon, not a sprint. Invest in training and education so your team understands both the opportunities and limitations of AI. Encourage learning through webinars, expert panels, and peer networks. The more informed your team is, the better positioned they’ll be to guide your organization strategically.
Why Organizations Must Act Now to Prepare for Artificial Intelligence
Although we may not yet be at AI’s Plateau of Productivity, waiting too long could hold your organization back. AI will, eventually, live up to most of the hype that surrounds it today. Whether it’s improving donor relationships, automating administrative work, or creating new avenues for advocacy, AI presents opportunities to augment how we work.
Take incremental steps today, and your organization could be well-prepared to reap the long-term benefits that AI promises. By proactively navigating through the Hype Cycle, you’ll be better equipped to lead your nonprofit into a future where AI is a key enabler of impact.
Start Building Artificial Intelligence Into Your Nonprofit
The future of AI in nonprofits, foundations, and associations is filled with potential, but action is needed to bridge the gap between hype and reality. Begin exploring ways to apply AI to your work by taking those first small steps today. Recognize that AI is not a panacea. Whether it’s testing tools for donor engagement or harnessing data for decision-making, incremental progress will set your organization up for the success AI can deliver.
