AI governance & adoption · Seller/servicers
Adopt AI once.
Govern it forever.
I help small and mid-sized seller/servicers adopt AI with governance built in so well that it's almost invisible to your team, but strong underneath.
What I bring
- Inside the GSE world
- 11 years at Fannie Mae, ending as Director of Multifamily Data & Analytics
- Adoption at scale
- 300+ applications and 1,000+ people moved onto a new cloud data platform
- Hands-on AI governance
- I run my own businesses on AI, with every tool inventoried, reviewed and approved
With Fannie Mae LL-2026-04 and Freddie Mac Guide §1302.8 in mindLeesburg, Virginia
AI is already in your shop
Most seller/servicers already use AI. Often it's built into vendor software, added in an update rather than chosen on purpose. Fannie Mae and Freddie Mac now expect you to know where it is, who's accountable for it, and how it's checked.1
Most small and mid-sized lenders don't have an AI team to sort that out. That's where I come in.
1 Fannie Mae, Lender Letter LL-2026-04: Governance framework on use of artificial intelligence and machine learning; Freddie Mac, Single-Family Seller/Servicer Guide, Section 1302.8.
How I help
Governance done right speeds adoption up.
Your team knows what's approved, what's safe to use, and how to bring in something new.
Find it
See where AI already is
A readiness review of the AI in your tools, vendors and everyday work, with the GSEs' new AI expectations in mind. You get a clear picture and a short, prioritized plan.
Set it up
Build governance that fits
An AI inventory your team can actually search, simple policies, vendor checks and a clear way to approve new tools. Sized for a lender your size, not a big bank.
Keep it current
Regular upkeep, so it never goes stale
Rules change, vendors add AI in updates, and staff try new tools. I set up AI that keeps your governance records current inside your own systems. Then we meet on a schedule that fits your size and needs to review what changed, work through exceptions and plan what's next.
The difference
Governance that doesn't get in the way
Good governance shouldn't feel like extra paperwork. I help you build it in so well that it's almost invisible to your team, but strong underneath. It becomes part of how the work already gets done, and the process makes sense. Set it up well in the beginning, and it's done for you later.
Exhibit 1Governance that keeps up with the work
01Things change every week
02Your framework catches each one
Built into how your team already works. Records stay current inside your own systems.
03Proof you can show tomorrow
- Policy updated to match the new guidance
- Call summaries: owner assigned, under review
- Drafting assistant: added to inventory, borrower-data rules shared
- Income tool: vendor checked, approved
Reuse and knowledge
Start with what you already have
Before anyone buys or builds something new, the inventory shows what's already approved and ready to use. Teams save time instead of starting from scratch, good tools get reused, and what one team learns, everyone can find.
Exhibit 2A new request, answered by the inventory
01Someone has an idea
Instead of buying a new tool or trying one on their own, they start with the inventory.
02The inventory looks first
Request looked up → match found → fit confirmed with the owner
03Reuse, not reinvent
Already approved. Start today.
- No new vendor to vet
- No new borrower-data risk
- The new use case is added, so the next person finds it too
No match? The request goes through a quick review, as in Exhibit 1.
A policy template gets you a document. Regular upkeep gets you proof you can show tomorrow.
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About Sandy Schaefer
I've spent my career helping people adopt new technology and making it trustworthy enough to use.
For 11 years at Fannie Mae, I led data governance and data platform teams, ending as Director of Multifamily Data & Analytics. I helped steward Fannie Mae's enterprise Property dataset, working with Legal, Privacy and InfoSec on its data-use rules. I know the GSE world from the inside.
I've also led adoption at scale. When Fannie Mae retired its legacy databases, I helped lead the move of 300+ applications and 1,000+ people onto a new AWS cloud data platform: explaining the change, making sure every team's processes and data needs were met, and tracking each one until it was fully moved and tested. After that, I cut SAFe PI Planning from five days to two across six-plus agile teams.
Before that, I built large systems as a consultant with Booz Allen Hamilton, CGI Federal and others, where rigor and documentation weren't optional.
Today my focus is AI governance and adoption management: putting a framework in place so every AI agent is registered, tracked and approved, with a clear understanding of the value it brings and the data it uses. It's the same adoption work in a new form: helping people go from waiting on a tech team to having AI that handles what they need, governed well from the start. I'm also a founder who runs my own businesses on AI, with every AI tool inventoried, reviewed and approved. I use what I recommend.
That mix of GSE experience, large-system delivery and hands-on AI governance is what I bring to your team: practical governance that helps your AI adoption move faster, not slower.
B.S. in Computer Science, George Mason University · Leesburg, Virginia
Let's talk
Book a 60-minute AI Governance & Adoption Strategy Consultation. We'll look at where AI shows up in your business today and what to do first.