For years, nonprofits relied on search engine optimization (SEO) to increase website visibility among donors via search engines. However, with the rise of generative AI tools like ChatGPT, Claude, and Google’s AI summaries, internet search dynamics have shifted significantly. “People use ChatGPT and similar AI tools like they would Google, ” explains Michael Yuasa, creative director at Antarctic, a marketing and fundraising firm. Users might seek volunteer opportunities at organizations fitting certain profiles directly through AI. Brittany Shaff, CEO of Shaff Fundraising Group, notes that 40% of searches now occur via generative AI platforms or AI-generated summaries on traditional search engines, making it crucial for nonprofits to ensure their presence in AI search results. Nevertheless, many nonprofits are currently absent from AI-based search outputs, warns Marc Ruben, partner at M+R, a marketing and fundraising firm. This absence means fewer website visitors and reduced opportunities to convert visitors into donors, advocates, or volunteers. To address this challenge, nonprofits must adopt new strategies beyond traditional SEO—which focused on keywords and tagging—and optimize their site data to align with how large language model AIs scan content. Experts explain the distinctions between SEO and AI search, what AI looks for, and the new opportunities AI search offers organizations. **How AI Search Differs from SEO** Traditional SEO helped build online reputations by emphasizing keywords and metadata. Shaff advises not to discard SEO entirely but to recognize the emerging field of generative engine optimization (GEO) or artificial engine optimization (AEO) as the new approach. Mark Koenig, chief innovation officer at Oregon State University, highlights that while SEO relied on tags and keywords, generative AI detects and adapts to attempts to manipulate it. Generative AI aims to answer user questions clearly and accessibly, favoring content with bullet points, plain language, and scannable formats rather than dense text. AI search can also interpret videos and audio—capabilities that traditional SEO lacks. Ruben summarizes the key difference: SEO drives traffic to a site, whereas AI platforms aim to answer questions directly within their interface without necessarily directing users to click through. **AI Prefers Clarity, Structure, and Emotional Relevance** AI systems seek content that can be quickly understood and summarized to answer user queries. Ruben stresses the importance of structured, readable content—using bullet points, lists, tables, and FAQ sections—to enhance AI comprehension. Shaff recommends clearly labeling and organizing frequently sought information (e. g. , "volunteer for X, Y, and Z") so AI can efficiently match content with user needs.

Ruben adds that AI favors consistent, standardized website structures using common terminology. Nonprofits should maintain straightforward pages like “Home, ” “About Us, ” “Donate, ” and “Contact Us, ” rather than creative but obscure titles like “Get to Know Us. ” Nirmal Kaur from Google Marketing Platform advises synthesizing website content using everyday language donors use and ensuring it meets E-E-A-T standards—Expertise, Experience, Authority, and Trustworthiness—to strengthen AI credibility. Unlike traditional search engines, AI also recognizes emotional context. Bharanidharan Natarajan, CTO at Antarctic, notes AI’s sensitivity to sentiment when generating responses. For example, if a query reflects frustration over finding free food assistance without shame, AI will prioritize content addressing those feelings. Yuasa points to testimonials as effective AI-friendly content, outlining problems, solutions, and impact with emotional resonance. **Opportunities in AI Search for Nonprofits** Nathan Chappell, founder of Fundraising. ai, views AI search not as a hurdle but as a new avenue to reach audiences. AI algorithms prioritize diverse content types—including voice and video—offering nonprofits an advantage if they utilize rich, varied media. This levels the playing field, allowing well-prepared nonprofits to gain visibility they might have lacked before. However, Chappell cautions that relying solely on static websites with sparse information and no multimedia limits visibility in AI search. Fortunately, AI does not require polished video; authentic smartphone-shot testimonials or event snippets are effective. Longer videos can be repurposed through generative AI into blogs or podcasts to diversify content engagement. Another benefit is that AI-driven traffic may convert better, as visitors come with higher trust and prior validation. Ruben explains that large language models (LLMs) may reinforce the organization’s credibility and effectiveness, leading to fewer but more engaged and motivated visitors likely to donate or volunteer. In summary, the rise of generative AI demands nonprofits evolve their online content strategy—structuring clear, accessible, emotionally relevant information and embracing diverse media—to thrive in this new search landscape and enhance donor engagement.