AI Agents for Donor Research: Automating Prospect Discovery and Qualification
Prospect research that once took four hours per donor can now take minutes. Agentic AI is not just speeding up existing processes. It is discovering prospects your team would never have found manually.
Traditional prospect research was defined by its limitations. A skilled researcher could profile perhaps five major gift prospects per day, pulling public records, scanning news archives, cross-referencing foundation databases, and synthesizing everything into a briefing document. It was painstaking work, essential to major gift fundraising, and chronically underfunded at most nonprofits. The average development department spent four hours or more researching each prospect before feeling ready to approach them.
That picture is changing rapidly. AI-powered prospect research tools can now generate comprehensive donor profiles in minutes. More significantly, a new generation of AI agents can do what traditional screening tools never could: actively discover prospects your organization has never encountered, scanning the public web in real time to surface individuals who match your ideal donor profile but have no existing relationship with your mission.
The 2026 Virtuous and Fundraising.AI benchmark survey of 346 nonprofits found that prospect research is among the most commonly adopted AI applications in development work, and that early adopters of agentic fundraising tools are saving four to six hours weekly on donor research while reporting meaningful increases in donor engagement. This guide covers how these tools work, what platforms offer the most practical value, how to think about ethics and privacy, and what AI genuinely cannot do that human relationship-builders must still handle.
What AI-Powered Prospect Research Actually Does
Understanding the full scope of what AI can do in prospect research requires distinguishing between three related but distinct capabilities that have emerged at different points in the technology's development.
Wealth Screening: The Established Foundation
Wealth screening is the oldest AI application in fundraising. Tools like DonorSearch and iWave (now Kindsight) analyze your existing donor database against hundreds of external data sources, including real estate records, SEC filings, political donation data, business ownership records, and philanthropic history from IRS Form 990 data. The result is a ranked list of your contacts scored by giving capacity, philanthropic inclination, and affinity to your cause.
DonorSearch's AI platform draws on over 1 billion data points updated weekly. iWave aggregates 44 vetted sources to build 360-degree donor profiles. These tools have been in use for years and have well-established track records. They are the starting point for any AI-assisted development program.
Prospect Profiling: AI That Builds Briefing Documents
The second generation of capability uses large language models to synthesize research into narrative briefing documents. Rather than presenting a spreadsheet of scores, these tools generate readable summaries that explain who a prospect is, what they care about, what their giving history suggests, and how they might be approached. LexisNexis's Nexis for Development Professionals draws on 81 billion public records to generate first-draft profile reports with full citations.
Dataro's ProspectAI represents this generation well: it "scans the web in real time, identifying publicly available information on prospects and compiling rich, executive-ready donor profiles in minutes," according to the company. The key distinction from static database screening is that these tools synthesize current web information rather than relying on periodic database refreshes.
Agentic Discovery: AI That Finds Prospects You Do Not Know
The newest and most transformative capability is AI that goes beyond your existing contact list to discover prospects who have no prior relationship with your organization. Rather than screening a list you uploaded, these agents actively search public data to find individuals matching your ideal donor profile, then qualify and surface the most promising ones for your team to pursue.
Salesforce Agentforce for Nonprofits (announced December 2025) includes a Prospect Research Agent integrated directly into Slack. Blackbaud's Development Agent operates proactively to manage portfolios and reach prospects that organizations could not previously reach at scale. Virtuous Momentum continuously mines CRM data to surface under-cultivated prospects that have been overlooked in existing relationships. Each of these represents AI moving from lookup tool to autonomous research partner.
What Data AI Analyzes to Qualify Prospects
Modern AI prospect research platforms pull from three primary categories of indicators, then layer in additional signals to build a multidimensional picture of each prospect's potential.
Capacity Indicators
Can they give?
Real estate ownership and property values
Stock holdings and SEC transaction filings
Business affiliations and ownership
Political donation history (FEC data)
Estimated household income
Wealth transfers and estate indicators
Philanthropic Indicators
Do they give?
Gifts to other nonprofits (IRS 990 data)
Average gift size, frequency, and recency
Types of causes historically supported
Board memberships at other organizations
Named giving history (buildings, endowments)
Foundation and trust affiliations
Affinity Indicators
Will they give to you?
Previous engagement with your organization
Volunteering or event attendance history
Connection to your mission area
Alumni or institutional relationships
Geographic proximity to your work
Public statements about related causes
Modern AI platforms combine these three dimensions into composite scores rather than relying on any single indicator. The key innovation is that AI can weight these factors dynamically based on your organization's specific donor patterns, rather than applying generic models built on other organizations' data. A wildlife conservation organization's top donor profile looks different from a workforce development nonprofit's, and AI platforms that learn from your historical data surface more relevant prospects.
Newer agentic tools add real-time layers on top of these established data categories: recent news coverage of a prospect's business activities, current philanthropic announcements, social media signals where relevant, and corporate social responsibility activities. This real-time dimension is particularly valuable for capturing wealth events such as business sales, IPOs, or inheritance situations that indicate a spike in giving capacity.
The Platform Landscape: Matching Tools to Organization Size
The AI prospect research market now serves organizations across a wide range of sizes and budgets. Understanding which tier of tools fits your situation helps avoid both overspending on capabilities you do not need and underinvesting in tools that could meaningfully expand your major gift program.
Enterprise Platforms: Comprehensive Coverage for Larger Development Programs
DonorSearch AI
DonorSearch has operated in the prospect research space for years and has integrated AI deeply into its platform. Its predictive modeling draws on over 1 billion data points updated weekly from dozens of sources. The AI generates standardized predictive models with point-and-click visualization, and its ProspectView Online 2 product uses generative AI to summarize the most actionable information from a prospect's profile. Organizations using DonorSearch have reported response rate increases of up to 85%, with many of those responses coming from previously overlooked or under-cultivated donors.
DonorSearch's approach emphasizes philanthropic indicators, specifically past giving to other organizations, which the platform treats as the strongest predictor of future giving. This philosophy contrasts with pure wealth screening tools that weight capacity data more heavily.
iWave (now Kindsight)
iWave, now operating under the Kindsight brand, offers 100 or more scores, analytics, and models drawing from 44 vetted data sources. The platform builds unified 360-degree donor profiles that blend wealth, philanthropic history, business, and relationship indicators into comprehensive prospect views. Real-time data access and customizable scoring models allow organizations to tailor the platform's outputs to their specific donor profile.
Kindsight also offers data enhancement services that clean and enrich your existing database before screening, which significantly improves matching rates and data quality for organizations with older or less complete CRM records.
Nexis for Development Professionals (LexisNexis)
LexisNexis's development-focused product draws on 81 billion public records from more than 10,000 sources, with generative AI tools that extract insights and generate first-draft research reports. The platform includes donor profiles combining giving history, affiliations, employment data, and visual summaries, plus media monitoring capabilities that track prospects in the news. It was named to the Best Non-Profit Software Products list in 2025. Pricing is tiered across Essentials, Premium, and Enterprise plans requiring custom quotes.
Mid-Market: Agentic Capabilities for Growing Programs
Dataro ProspectAI
Dataro's ProspectAI is a newer entrant that exemplifies the agentic shift in prospect research. Rather than static database screening, ProspectAI functions as a "virtual research assistant that scans the web in real time, identifying publicly available information on prospects and compiling rich, executive-ready donor profiles in minutes," according to the company. The platform uses large language model technology to synthesize publicly available information as it exists today, not as it existed when a database was last updated.
Dataro starts at $250 per month, making it among the more accessible dedicated AI prospect research tools. It integrates with Virtuous CRM and multiple other platforms, and more than 300 leading nonprofits use some part of Dataro's broader product suite. The company also offers AI-powered revenue forecasting and future giving predictions, allowing organizations to anticipate donor behavior rather than simply respond to it.
Salesforce Agentforce for Nonprofits
Announced in December 2025, Salesforce's Agentforce for Nonprofits includes a dedicated Prospect Research Agent integrated directly into Slack, where fundraisers already prepare for donor meetings. The agent autonomously surfaces relevant prospect information, drafts briefing documents, and suggests talking points based on a prospect's giving history and interests. Ask-Assist functionality allows gift officers to query their donor data using natural language rather than database reports.
For organizations already on Salesforce Nonprofit Cloud, Agentforce represents the most frictionless path to AI prospect research since it operates within existing workflows. Nonprofit Cloud starts at approximately $36 per user per month, with up to 10 free licenses available through the Power of Us program for eligible nonprofits. Agentforce interactions are priced separately at approximately $2 to $5 per conversation.
Blackbaud Raiser's Edge NXT with Development Agent
Blackbaud has embedded AI across Raiser's Edge NXT through a series of releases in late 2025. Prospect Insights provides AI prescriptive actions within the CRM for major giving likelihood. Prospect Insights Pro adds pipeline identification for future major gift prospects and planned giving insights. The newest addition, Development Agent, is described by Blackbaud as "the very first of our Agents for Good," operating proactively to manage donor portfolios and reach prospects organizations could not previously reach at scale. Chat for Blackbaud AI allows natural language queries about constituent data within the CRM.
Accessible Options: AI Prospect Research on Tighter Budgets
Dedicated enterprise prospect research platforms can be cost-prohibitive for smaller organizations. Several paths offer meaningful AI-assisted research at lower price points.
Deep Research Tools
OpenAI's Deep Research (10 uses/month on ChatGPT Plus), Perplexity Deep Research (free with limited queries, $20/month Pro), and Google's Deep Research mode autonomously browse dozens of sources and synthesize research reports with citations. These general-purpose tools can conduct prospect research on specific individuals, compiling publicly available information into briefing documents without a dedicated platform.
Virtuous CRM with Momentum
Virtuous CRM with the Momentum add-on offers AI-powered portfolio prioritization, personalized communication drafting, donor plan creation, and automatic CRM logging. Integrates with Dataro for predictive analytics. Targeted at mid-size organizations that need agentic capabilities without enterprise platform pricing.
General AI Assistants for Manual Research
Claude, ChatGPT, and similar AI assistants can support manual prospect research by drafting profiles from information you gather, synthesizing research into briefing documents, identifying patterns in giving histories, and suggesting cultivation strategies based on prospect characteristics. Free or low-cost, requires more staff time but works for small prospect pools.
Dataro at Entry Level
At $250/month, Dataro ProspectAI is the most affordable dedicated agentic prospect research tool with real-time web scanning capabilities. For organizations with an active major gifts program that need more than general AI tools but cannot justify enterprise pricing, this represents a practical entry point.
Note: Prices may be outdated or inaccurate.
A Practical Workflow: AI-Assisted Prospect Research Step by Step
Understanding how AI prospect research works in practice helps development teams set realistic expectations and design workflows that integrate AI appropriately alongside human judgment.
Data Enrichment
Upload your donor database to a platform like DonorSearch or iWave. The system enriches every record with up to 90 pieces of new information pulled from third-party public data sources. Contact records that previously contained only names and addresses now include wealth indicators, philanthropic history, and affinity signals. This single step can fundamentally change how your team prioritizes outreach.
AI Scoring and Portfolio Prioritization
AI runs predictive models on your enriched database, scoring and ranking every contact. Major gift officers receive a prioritized portfolio view in minutes, compared to the average four-hour monthly manual portfolio review process that many development teams previously conducted. The AI flags prospects with the highest combination of capacity, philanthropic history, and affinity scores for immediate attention.
New Prospect Discovery
Lookalike modeling and network analysis surface prospects your team has not yet identified. AI analyzes your existing major donors' characteristics and searches public data for individuals who match that profile but have no prior relationship with your organization. Agentic tools like Dataro ProspectAI can surface approximately 20 qualified new prospects per week through continuous web scanning, according to the company's reported outcomes.
Profile Generation
For high-priority prospects, AI generates comprehensive briefing documents. Previously this required two to four hours of manual research per prospect. With AI tools, the initial profile arrives in minutes, covering philanthropic history, wealth indicators, business and board affiliations, news coverage, and suggested talking points. LexisNexis generates first-draft reports with full citations for staff review, treating the AI output as a starting point rather than a final product.
Ask Brief Preparation
AI drafts meeting preparation briefs, suggesting talking points and ask amounts based on a prospect's giving capacity, philanthropic history, and interests. Salesforce Agentforce's Ask-Assist functionality drafts hyper-personalized ask briefs that, according to the company, increase meeting-to-gift close rates for early adopters. Gift officers review and refine these drafts based on relationship knowledge that AI cannot access.
Outreach Personalization
AI drafts personalized communications based on prospect profiles. Rather than sending generic appeals, gift officers can send outreach that references a prospect's specific philanthropic interests, recent business activities, or connections to the cause. The AI generates the first draft; the gift officer applies relationship knowledge and finalizes before sending.
CRM Logging and Follow-Up Triggers
Agentic tools automatically log outreach activities back to the CRM and trigger follow-up workflows based on engagement signals. Rather than relying on gift officers to manually log every interaction and set calendar reminders, AI maintains portfolio momentum through automated activity tracking and intelligent follow-up prompting.
Privacy, Ethics, and Donor Trust: What Your Team Must Consider
The capabilities of AI prospect research come with real ethical obligations that development teams cannot afford to ignore. The 2025 Fundraising.AI Donor Perceptions survey of over 1,000 donors found that privacy and data security concerns are named by two-thirds of donors as key worries. Thirty-two percent of donors say they would give less to an AI-enabled organization, while 14% would give more. Transparency in AI use has shifted, according to the survey, "from reassurance to requirement."
Consent and Awareness
Prospect research using publicly available information has a long history in fundraising, and the field generally treats public data as appropriate to use. But AI enables a depth of profiling that was previously not practical, and organizations should ask honestly whether the level of detail AI generates would feel intrusive to prospects if they knew it was happening. Developing clear policies about what data is appropriate to gather, how it is stored, and how long it is retained is an important governance step before deploying these tools at scale.
Algorithmic Bias in Prospect Discovery
AI lookalike models trained on your historical major donor data will surface more people who resemble your existing major donors. If your historical major donors skew toward particular demographics, geographies, or networks, AI will reinforce rather than correct that pattern. The 2025 sector equity report found that 64% of nonprofits are aware of AI bias issues (up from 44% in 2024), but only 36% have implemented actual equity practices (down from 46% in 2024). Development teams should actively evaluate whether AI prospect discovery is broadening or narrowing their donor network.
Data Accuracy Requires Human Review
AI-generated profiles contain errors that human review must catch. Researchers have documented instances where AI flagged smaller nonprofits as "hiding financial information" because they file shorter 990-N forms rather than full Form 990s, a complete misinterpretation of normal compliance behavior. Slightly incorrect organization names, outdated job titles, and references to foundation names that have changed are common in AI-generated profiles. Treating AI output as a starting point requiring human validation, rather than a final product, is the appropriate workflow design.
GDPR Compliance for International Donors
Organizations collecting or managing personal information about anyone based in the EU or EEA must comply with GDPR. Non-compliance carries fines up to 20 million euros or 4% of annual revenue. Prospect research on EU-based individuals using AI tools requires careful legal review, as the level of profiling that AI enables may fall under GDPR's definitions of processing that requires explicit legal basis beyond legitimate interest.
DonorSearch publishes a Responsible AI framework that offers one model for thinking about ethical use. The underlying principle is to use AI to identify individuals who might genuinely care about your mission, not to manipulate or pressure people who have not expressed interest. The distinction between identifying potential affinity and pursuing prospects who have signaled no interest is one that human judgment, not AI, must make.
What AI Cannot Do: The Irreplaceable Role of Human Relationship-Building
Research sources and experienced gift officers are consistent and emphatic on this point: AI is a powerful assistant for research and triage, but it cannot replace the human dimensions of major gift fundraising. Understanding these limitations is as important as understanding the capabilities.
A 2025 peer-reviewed study in the Journal of Marketing found that donors respond differently to AI-identified fundraising appeals than to human-identified ones. Narrative perspective and the perceived identity of the relationship-builder influence donation intentions in ways that purely AI-managed outreach cannot replicate. This is not a temporary limitation of current technology. It reflects something fundamental about how major donors make decisions about significant gifts.
Emotional Readiness Assessment
AI cannot assess whether a prospect is emotionally ready to make a major gift, regardless of their wealth or philanthropic history. Relationship timing requires human intuition about grief, family transitions, business cycles, and personal priorities.
Relationship History and Dynamics
The full context of how a relationship developed, including small interactions, perceived slights, sources of inspiration, and trust built over years, lives in people, not in CRM records. Gift officers carry institutional knowledge that AI cannot access.
Authentic Passion for Mission
Conveying genuine commitment to the mission in a way that inspires transformational giving requires a human who is genuinely invested. AI can draft eloquent appeals, but prospects considering six-figure gifts have sophisticated antennae for authenticity.
Restraint as a Strategy
Knowing when not to ask, when to wait, or when to let a relationship breathe rather than advance it is a judgment call that requires understanding of relationship dynamics. AI optimizes for engagement signals; sometimes the right cultivation move is deliberate patience.
Responding to Unexpected Signals
A prospect who mentions a family health crisis, a business challenge, or a personal loss requires a human response that prioritizes the relationship over the pipeline. AI cannot read these situations with the judgment that maintains long-term trust.
Ethical Judgment About Individual Cases
Some prospects may be technically highly qualified but unsuitable for cultivation due to organizational conflicts, values misalignment, or reputational concerns that require contextual judgment beyond data scoring.
The most experienced gift officers describe their relationship with AI prospect research tools the same way: "Think of AI as a high-powered research assistant, not a fundraising partner." AI excels at pattern recognition, data processing, and information synthesis at scale. It compresses weeks of manual research into hours, surfaces prospects that would otherwise be missed, and ensures that gift officers walk into donor meetings fully briefed. But the art of major gift fundraising, which is ultimately about building relationships with people who care deeply about a cause, remains irreducibly human.
What Is Driving Adoption in 2026
Several converging forces are accelerating adoption of AI prospect research tools across the nonprofit sector in 2026.
Platform Consolidation Into CRM Workflows
The dominant trend is AI prospect research capabilities moving directly into the CRM where gift officers already work, rather than requiring separate platforms. Salesforce Agentforce in Slack, Blackbaud Development Agent in RENXT, and Virtuous Momentum in their CRM all represent this integration-first approach. The friction of exporting and importing data between systems was a significant adoption barrier. Eliminating it by building research capabilities into existing tools is dramatically lowering the entry cost of AI-assisted prospect research.
Real-Time Web Research Replacing Static Databases
Traditional screening tools rely on databases updated on weekly or monthly cycles. This creates gaps for organizations trying to identify recent wealth events such as business exits, IPOs, or inheritance situations. Dataro ProspectAI and Salesforce Agentforce represent a new approach: real-time web scanning that surfaces current public information. For nonprofits tracking the wealth landscape actively, this difference matters significantly for high-opportunity prospect identification.
The Federal Funding Shift Is Driving Prospecting Urgency
With reduced federal funding affecting many nonprofit program areas, organizations are under intense pressure to diversify revenue sources toward individual major donors and foundations. Fast Company reported in 2025 that agentic AI is specifically helping organizations find new funding sources that they would not have discovered through traditional network-based approaches. This external pressure is creating urgency around prospect research that might otherwise have evolved more slowly.
Getting Started: First Steps for Development Teams
The 2026 Virtuous and Fundraising.AI survey found that 92% of nonprofits now use AI, but only 7% report major improvements in organizational capability. The gap is not about access to tools. It is about implementation depth. Development teams that want to close that gap should start with structured, deliberate steps rather than tool adoption for its own sake.
Audit Your Current Prospect Research Process
Before selecting any tool, document how your team currently conducts prospect research. How much time does it take? Where are the bottlenecks? How many prospects does your team research per week? What information do you wish you had before major gift meetings? This baseline makes it possible to evaluate tools against your actual needs rather than their feature lists.
Start with Your Existing Database
The highest-leverage starting point for most nonprofits is enriching your existing donor database with AI-powered wealth screening rather than pursuing new prospect discovery. Understanding the major gift potential within your existing network typically reveals opportunities that can be pursued immediately, before investing in agentic discovery tools.
Pilot with One Gift Officer's Portfolio
Rather than deploying AI prospect research organization-wide, pilot it with one development officer's portfolio over 90 days. Measure time savings, profile quality, and whether AI-surfaced prospects convert to meetings and gifts at comparable rates to manually researched prospects. This generates evidence for broader adoption decisions and surfaces any workflow issues before they affect the full team.
Develop a Data Quality Policy Before You Need One
AI prospect research tools surface and store significant personal data about individuals who have not consented to this process. Before deploying these tools at scale, establish clear policies about data retention, who can access prospect profiles, how errors in AI-generated profiles are corrected, and how you handle requests from individuals who ask what information you hold about them.
Treat AI Output as a Starting Point, Not a Conclusion
Design workflows that explicitly require human review of AI-generated profiles before action. The gift officer who will cultivate the relationship should read every AI-generated profile critically, identify potential errors or missing context, and add relationship knowledge that AI cannot access. The fastest path to AI prospect research failures is treating automated outputs as reliable without verification.
The Bottom Line for Development Professionals
AI prospect research has moved well past the experimental stage. Dedicated platforms from DonorSearch, iWave, Dataro, Blackbaud, and Salesforce offer documented productivity gains and prospect discovery capabilities that were not practically available three years ago. The shift from static database screening to agentic, real-time web research represents a meaningful capability upgrade for development programs at any scale.
At the same time, the 2026 adoption data reveals a sector that is experimenting more than it is transforming. Organizations that use AI for individual tasks without integrating it into shared development workflows, without governance frameworks for data quality and ethics, and without realistic expectations about what AI cannot do, will see modest gains. Organizations that deploy these tools with clear processes, human review requirements, and honest assessment of the relationship dimensions that remain irreducibly human will see the substantive improvements early adopters are already reporting.
The best development programs will use AI to surface more prospects, understand them more deeply, and prepare gift officers more thoroughly, while investing the time freed by AI efficiency into the relationship-building conversations that no algorithm can have for them.
Ready to Transform Your Major Gifts Program?
We help nonprofits evaluate AI fundraising tools, design prospect research workflows, and build the development capacity to convert more prospects to major donors.