How AI Is Transforming Planned Giving: Identifying Legacy Gift Prospects at Scale

Planned giving, the practice of encouraging donors to include your organization in their estate plans, has always been one of the most impactful and most neglected corners of nonprofit fundraising. Bequests and other legacy gifts totaled $45.84 billion in 2024, representing nearly 8% of all U.S. charitable giving, according to Giving USA 2025. Yet only about 25% of nonprofits actively cultivate planned gifts, leaving an enormous opportunity on the table.

The gap between opportunity and action comes down to two familiar challenges: capacity and identification. Most development teams are stretched thin managing annual fund campaigns, grant deadlines, and major gift cultivation. Planned giving requires a longer time horizon, more patient relationship-building, and a fundamentally different kind of prospect research. Identifying who is likely to leave a bequest has historically been more art than science, relying on the intuition of experienced fundraisers who know which long-tenured donors to call.

AI is changing the equation on both fronts. Predictive models can now screen entire donor databases and continuously surface planned giving prospects based on behavioral signals that human analysts would never have time to synthesize. Generative AI tools help development officers craft personalized outreach that speaks to each donor's history and motivations. And the urgency is growing: Cerulli Associates estimates $124 trillion in assets will change hands by 2048, with more than $12 trillion projected to flow to charitable organizations. The nonprofits best positioned to capture a share of that wealth transfer will be those that start building their planned giving programs now, with the help of AI.

This article explores how AI is being applied to planned giving, what signals it analyzes to identify prospects, which tools and platforms are leading the field, and how nonprofits of all sizes can begin building more effective legacy giving programs without a dedicated planned giving officer on staff.

One nuance worth understanding: AI models are only as good as the data you feed them. Nonprofits with inconsistent CRM data, where engagement records are incomplete or contact information is outdated, will get less accurate results. Before investing in AI-powered prospect screening, it is worth conducting a data hygiene assessment to understand what signals are actually captured in your donor database. This connects directly to the broader case for treating your data as a strategic asset across every aspect of your organization.

Predictive AI tells you who to talk to. Generative AI is changing how you prepare for that conversation. In 2026, the most advanced platforms are merging these two capabilities into unified development workflows: a development officer opens their CRM and finds a ranked list of planned giving prospects alongside AI-drafted, personalized outreach messages that reflect each donor's history, engagement patterns, and apparent interests.

For smaller organizations without these integrated platforms, there is still significant value in using generative AI as a preparation tool. Before a cultivation call or meeting with a long-tenured donor, a development officer can use a tool like Claude or ChatGPT to synthesize the donor's giving history, summarize recent organizational milestones that might be relevant to share, draft a thoughtful letter or email, and prepare responses to common questions about planned giving vehicles like charitable remainder trusts, charitable gift annuities, and beneficiary designations.

Natural language processing tools are also being applied to analyze existing communications between donors and development staff, surfacing signals of planned giving interest that might otherwise be missed. A donor who asked a question about estate planning in an email three years ago, or who mentioned their children had moved out, may be surfaced as a high-priority planned giving prospect based on those conversational signals. This kind of analysis requires careful attention to data governance and privacy, since donor correspondence is sensitive and should be handled accordingly.

The critical principle to maintain, regardless of how sophisticated the AI tools become, is that planned giving is a relationship business. No planned giving conversation should be initiated or conducted by an AI acting as a human representative. AI should prepare and equip development officers, not replace the human relationships that ultimately lead donors to trust an organization with part of their legacy. This aligns with what the most effective AI implementations share across the sector: technology augments human judgment rather than substituting for it.

One reason planned giving programs go underfunded is that their success is genuinely difficult to measure on the timelines that boards and executive leadership typically care about. A bequest that results from a cultivation relationship built today may not materialize for 20 years. This disconnect between investment and return creates real organizational pressure to deprioritize planned giving in favor of programs that show immediate results.

AI can help address this by surfacing leading indicators that serve as proxies for program health before realized gifts arrive. Number of qualified planned giving conversations initiated, number of donors added to legacy society acknowledgment programs, number of gift intent forms completed, and changes in planned giving prospect scores over time all provide meaningful signals about program momentum without requiring realized gifts.

The ROI data, when realized gifts do come in, is compelling. FreeWill's platform data shows $56.83 returned for every $1 invested in planned giving programs, a ratio that far exceeds most other fundraising channels. Building that case with leadership, supported by leading indicators and AI-identified prospect pipeline data, is increasingly how planned giving officers are winning the internal budget arguments that sustained programs require.

For organizations ready to begin integrating AI more broadly into their fundraising and donor stewardship functions, planned giving prospecting is one of the highest-ROI applications available. It pairs well with other AI-driven donor intelligence approaches, including the behavioral analytics that reveal deeper donor intent signals, and with the organizational knowledge management practices that ensure development insights are captured and shared across your team rather than living only in the heads of individual officers.