Major Gift Officer
Research and qualify new major gift prospects
What You Do Today
Identify new prospects through wealth screening, event attendance, annual fund upgrades, and board referrals. Research capacity indicators and connection points to qualify prospects for portfolio inclusion.
AI That Applies
AI performs wealth screening using public data sources, identifies giving patterns to peer organizations, and scores prospects by affinity, capacity, and accessibility.
Technologies
How It Works
The system ingests public data sources as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.
What Changes
Prospect identification and capacity analysis become dramatically more efficient with AI processing public wealth indicators.
What Stays
Qualifying whether a wealthy prospect actually has philanthropic motivation for your mission, and determining the right approach to initiate a relationship, require human discernment and social intelligence.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for research and qualify new major gift prospects, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long research and qualify new major gift prospects takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your VP Operations or COO
“What data do we already have that could improve how we handle research and qualify new major gift prospects?”
They're prioritizing which operational processes to automate
your process improvement or lean lead
“Who on our team has the deepest experience with research and qualify new major gift prospects, and what tools are they already using?”
They understand the workflow dependencies that AI tools need to respect
a frontline supervisor
“If we brought in AI tools for research and qualify new major gift prospects, what would we measure before and after to know it actually helped?”
They see the daily reality that AI tools need to fit into
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.