By George Irish
2024 was another landmark year for artificial intelligence, capped off in just the past few weeks with big advancements in real-time AI voice conversations, Hollywood-quality video generators, and AI Agent-automated work processes. As we enter 2025, AI’s rapid evolution shows no signs of slowing down – and nonprofits and charities face a daunting task trying to keep up.
Recent research from the Charity Insights Canada Project (https://carleton.ca/cicp-pcpob/) paints a concerning picture: in their Oct 2024 survey of 143 Canadian nonprofits and charities, only 18 percent of respondents feel fully confident in their readiness to use AI. Another 17 percent report being “somewhat” confident, leaving the majority of organizations uncertain about how to move forward in this rapidly changing landscape.
2025: Your Year of AI Action
The post-holiday period is an ideal time to kick-off your organization’s AI adoption strategy.
AI’s evolution is happening at a rapid pace compared with earlier tech waves like the internet or social media. It brings many of the same issues of privacy, security, and job adaptation, but it also adds unique concerns like copyright grey zones, the ethical implications of automated decision-making, and new oversight requirements.
These challenges are significant but manageable with the right approach, and the potential benefits are already clear. According to the Charity Insights Canada Project, forward-thinking nonprofits already recognize AI’s transformative potential:
- 58 percent believe AI can dramatically improve their data analysis capabilities,
- 55 percent see opportunities in AI-powered content creation, and
- 50 percent recognize AI’s potential to enhance program targeting.
Three trends from 2024 that will shape AI in 2025
AI Hesitation continues to hold organizations back. This hesitation has real consequences: reduced operational efficiency, missed fundraising opportunities, and diminishing competitiveness in the battle for donor attention. Organizations that delay action may find themselves unable to meet rising stakeholder expectations for personalized engagement and data-driven decision making – expectations being shaped by their supporters’ experiences with AI-savvy commercial brands.
Secret Cyborgs are growing in many organizations – staff members quietly using personal AI accounts for work tasks without official approval. This “Bring Your Own AI” trend creates security and reputational risks while preventing organizations from sharing valuable learnings. Rather than ignoring this trend, organizations need to acknowledge and address it through clear policies and supported adoption strategies.
AI Integration is becoming ubiquitous. AI-powered features are now embedded in virtually every digital tool, from donor CRMs to video conferencing platforms. While ChatGPT is still the ‘go-to’ AI app, we’re also seeing new specialized AI apps designed specifically for nonprofit workflows with seamless integration into existing systems. Organizations that understand and embrace these integrations will be better positioned to leverage AI’s benefits.
Your 2025 AI To-do ListWith these trends in mind, here’s a practical roadmap to help your organization move from AI hesitation to meaningful adoption in 2025.
1. Start the AI Conversation now
Success with AI begins with getting people talking across your organization about what’s possible. Your fundraising team might be wondering if AI could help identify donors at risk of lapsing. Your communications team is probably already experimenting with AI writing tools. Each department sees different possibilities and faces different challenges.
The key is bringing these perspectives together naturally. Start with informal discussions during team meetings or lunch-and-learns where people can share their experiences and ideas. These organic conversations often reveal unexpected connections – like how donor engagement patterns might inform program delivery, or how program impact stories could enhance fundraising appeals.
Let these discussions flow naturally into collaboration. Some organizations find that informal cross-department AI sharing sessions help everyone learn together. Others create channels where staff can share AI tools and techniques they’re discovering, or an AI Task Force or Safety Committee.
What matters isn’t the structure, but creating spaces where people feel comfortable exploring possibilities together.
2. Identify your Focus Areas
Rather than attempting to transform everything at once, your AI journey should begin where it can provide the most valuable learnings. Look first to departments that have demonstrated enthusiasm for innovation and where you already have strong data foundations. Consider areas facing pressing operational challenges that AI could help address.
The key is finding innovation-ready opportunities that align with your strategic priorities. For instance, if donor retention is currently a focus area, explore AI projects that could enhance personalization and engagement in your donor communications.
3. Get Help
The AI landscape is complex and fast-moving, and you shouldn’t try to navigate it alone. Start by asking your current technology vendors and agencies about their own AI roadmaps and available features. Many are already developing AI capabilities that could benefit your organization.
Professional associations and nonprofit technology groups are also increasingly offering AI-focused workshops, webinars, and communities of practice. These collaborative learning opportunities can provide both practical insights and strategic grounding as your team navigates the AI landscape.
For more structured guidance, consider bringing in specialized nonprofit AI consultants who understand both the technology and the unique challenges of the sector. As well, investing in AI literacy training for staff can help build internal capacity and understanding.
4. Start Piloting
The key to AI success may not be in extensive research, but rather learning through doing. Start with small, contained experiments where the stakes are low and the potential for learning is high. Think of each pilot as a chance to explore and understand, not a make-or-break initiative. Some of your most valuable insights might come from projects that don’t work out as planned.
Keep your initial experiments focused and manageable. Choose areas where you can test AI solutions without disrupting critical operations. For example, try using AI to analyze historical data before applying it to current decisions, or test new AI-powered content tools on internal communications before using them for donor outreach.
Remember that “failure” in a pilot project isn’t really failure – it’s valuable information about what works, what doesn’t, and why. Each experiment, regardless of outcome, builds your organization’s understanding of AI’s potential and limitations.
Eight Practical Pilots to Kick-off Your AI Journey:
Here are eight practical pilots that organizations can implement with minimal disruption to existing operations.
Core Fundraising Pilots
Let’s start with four fundraising pilots that leverage AI to enhance traditional development work, building on your existing donor data and relationships:
The Donor Reactivation Predictor offers a low-risk entry point into AI-powered fundraising. This pilot uses AI to analyze your lapsed donor data from the past 2-3 years, identifying patterns among those who have successfully reactivated. The goal isn’t to completely automate reactivation, but to help your team work smarter by focusing their efforts on the most promising opportunities. Even a small improvement in reactivation rates can justify the experiment.
The Event ROI Optimizer addresses a common challenge: maximizing the return on fundraising events. This pilot analyzes historical event data – costs, attendance, giving outcomes, and follow-up success – to identify what drives success. Start with data from just one type of event, looking for patterns that could inform future planning. The insights gained can immediately improve your next event’s planning process.
The Mid-Level Donor Pipeline Identifier offers a strategic approach to strengthen mid-level giving programs. This pilot uses AI to analyze giving histories and engagement patterns, identifying regular donors showing similar characteristics to those who successfully transitioned to mid-level giving. Begin with a small test group, allowing your relationship managers to validate and refine the AI’s recommendations.
The Donor Segmentation Enhancer amplifies the precision of creating targetable donor segments. Use AI to analyze your entire donor data, uncovering nuanced patterns and refining traditional segments like age, income, and giving history with behavioural and engagement insights. Fundraisers review and validate these AI-driven segments, ensuring they are actionable and aligned with campaign goals. Their feedback will help improve segmentation strategies for future campaigns.
Digital Fundraising Pilots
Digital fundraising is an area of constant innovation, and it is highly likely that your digital fundraisers (or your agency partners) have already been educating themselves and experimenting with AI-powered fundraising tools and tactics
The Email Appeal Optimizer provides a structured way to improve email campaign performance. Rather than making wholesale changes to your email strategy, start by using AI to analyze and optimize one specific type of appeal – like monthly giving requests. Generate multiple versions for testing, always keeping your brand voice and donor engagement principles in mind.
The Social Donor Journey Mapper analyzes how supporters move from social media engagement into the giving funnel and convert to financial supporters. Begin with just one platform, using AI to identify patterns in supporter behaviour that lead to donations. This insight can help your team better time and target their social media appeals.
The Landing Page Personalizer experiments with adapting donation page content based on how visitors arrive at your site. Start small by testing personalization on one or two key landing pages, measuring the impact on conversion rates. This pilot can demonstrate the potential of AI-driven personalization while containing any risks.
The Supporter Services ChatBot explores AI’s potential to enhance donor service. Begin with a clearly defined scope – perhaps handling common donation process questions during off-hours. Human oversight remains essential, ensuring responses align with your organization’s voice and values.
You can find additional descriptions of AI pilot projects on my website at: www.FundraisingwithAI.com.
Learning from Your Pilots
Remember that these pilots are as much about organizational learning as they are about immediate results. Document both successes and setbacks, share insights across teams, and use what you learn to inform your next steps. The goal is to build your organization’s AI capabilities while managing risks and resources effectively.
Successful pilots often lead to unexpected insights. For example, an email optimization pilot may reveal broader insights about donor communication preferences for your entire digital strategy. A grant matching pilot could highlight data quality issues that, once addressed, improve multiple aspects of your operations.
The key is to start somewhere, learn actively, and build on your successes. Choose the pilot that best aligns with your current priorities and capabilities, and don’t wait for perfect conditions to begin. The magic word is: Pilot.
George Irish is a veteran of strategy, coaching and consulting for AI-powered charity fundraising. He works with Amnesty International Canada and Greenpeace, among other organizations. He writes this column exclusively for each issue of Foundation Magazine.
Related Posts
