The economics of alumni fundraising have always been brutal. A typical advancement office manages a pool of tens of thousands of alumni. Major gift officers can meaningfully cultivate perhaps 150 relationships each. Annual fund staff are responsible for the rest, and 'responsible' often means one bulk email in October and another in December.
The result is predictable. Participation rates at most institutions hover between 8% and 12%. The vast majority of alumni never give, not because they don't care about their alma mater, but because they've never received an outreach that felt personal enough to warrant a response.
At One Public University, a Risely partner institution, the math was even tighter than usual. A single prospect researcher supported six gift officers, each managing 150 to 170 households across an alumni and parent base of more than 60,000. The institution had just exceeded a $250 million campaign goal, foundation reporting volume had grown sixfold in recent years, and the researcher's queue was permanently jammed with urgent ad-hoc requests. The strategic, judgment-driven research that actually moves campaigns was being squeezed out by the assembly work needed to keep the existing pipeline alive.
4×
More strategic research capacity
66 sec
To draft a prospect brief, down from 2 hours
121
Net-new prospect briefs in 12 weeks
$250M+
Campaign goal exceeded
6×
Growth in foundation reporting volume
What Personalization at Scale Actually Means
When advancement professionals talk about personalization, they usually mean variable field insertion: swapping in a graduate's name, class year, and major. Risely's AI advancement agents operate at a different level entirely.
The agent draws on a rich alumni data profile that includes engagement history, event attendance, social media signals, employment changes (via LinkedIn integration), and giving history. It uses this data to determine not just what to say, but when to say it, through which channel, and with which ask amount, all calibrated to maximize the probability of a positive response.
A 2019 graduate who just got promoted to a VP role at a tech company is a different conversation than a 2019 graduate who just moved across the country and attended their first alumni happy hour. The agent knows the difference.
Most consequentially, the work that used to take a researcher two hours, drafting the prospect framework that gives a gift officer a starting point on a new donor, now takes the agent 66 seconds. At One Public University, that single shift produced 121 fully drafted prospect briefs in the first 12 weeks. Before Risely, none of them would have existed.
The Ask Strategy Problem
One of the most underappreciated drivers of low giving rates is ask misalignment. A $500 ask to a recent graduate with student debt triggers an immediate deletion. A $25 ask to an alumnus who gave $2,500 last year signals institutional disorganization and mild insult.
AI advancement agents solve this through dynamic ask modeling. The agent analyzes an alumnus's full giving history, wealth indicators, recent life events, and peer comparisons to generate a personalized ask range, then picks the specific ask amount most likely to result in a gift at or above baseline.
At one Risely partner institution, implementing AI-driven ask optimization alone increased average gift size by 18% without any increase in outreach volume.
From Assembly Work to Judgment Work
The biggest change AI advancement agents bring isn't the speed. It's what they free advancement professionals to actually do.
Before Risely, the prospect researcher at One Public University, a 20-year veteran of the role, spent most of the week on what they called assembly work: pulling LinkedIn profiles, cross-referencing wealth indicators, formatting briefing documents, drafting initial frameworks for upcoming meetings. Necessary tasks, but not the parts of the job that two decades of experience uniquely qualify someone to do.
Once the agent took over the assembly work, the week reorganized itself. Portfolio-wide strategy reviews, the kind that surface patterns across hundreds of donors at once, became a weekly habit instead of a stretch goal. Same-day responsiveness to gift officer requests, which used to be impossible, became the default. Event briefings that previously took one to two hours apiece now took minutes, because the agent had already drafted the foundation before the researcher opened the file.
The VP of Advancement put it directly: 'The work itself changed, not just the speed of it.'
The team's effective research capacity multiplied by four, not because anyone worked longer hours, but because every hour now went toward judgment instead of assembly.
The Metrics That Matter
Risely advancement agent deployments consistently produce three measurable outcomes: higher participation rates (typically 4 to 8 percentage points above baseline), higher average gift size (15% to 22% above prior cycle), and an expanded major gift pipeline (2 to 3 times the number of donors identified as major gift ready).
For One Public University, the numerical story was sharper still: 4 times the research capacity, 121 net-new prospect briefs in 12 weeks, and a researcher who finally had the bandwidth to do the strategic work that gift officers had been requesting for years.
For a mid-size institution with 40,000 alumni and a $2 million annual fund goal, these improvements can translate to $400,000 to $700,000 in incremental revenue per year, at a fraction of the cost of additional advancement staff.