Hidden away in some of our histories is a stint in commercial real estate. Just enough experience to be effective but no longer a practice focus—and by this, I mean real estate agents, just like attorneys and doctors, practice what we do on a daily basis. There are a few who do it all equally well, but for the rest of us we specialize. The language is different, the reasons are different, but the money is the same.
You get an offering memorandum (OM). 12 pages of financial data and maps. You skim it. You tell your client, "Looks solid." You have no idea if it's solid. You just didn't want to have to spend half an hour on a search engine trying to figure out what GRM means
This is how agents lose all credibility with investors—when you don't know the difference between GRM, DSCR, and NOI, you definitely don't account for how a loan changes the whole picture; but investor clients do know; they know Excel.
That's how you lose clients; they figure out you didn't read beyond the listing agent's pro forma cheerleading.
Here's the shortcut that doesn't require dancing around the truth.
Upload and Prompt
Upload the OM to an AI assistant of your choice, most of the pro or plus plans allow unlimited document uploads.
Paste this:
"Analyze this offering memorandum and give me: (1) Property type and location, (2) Purchase price, (3) Current annual income and expenses, (4) Tenant lease expiration dates—highlight any below-market rents, (5) Any capital needs over the next 5 years, (6) The three biggest risks this memo either flags or hides, and (7) The three questions I'm asking the seller's broker before my client moves forward."
What Comes Back
AI spits out something organized. Not perfect. But organized.
Property: 12-unit multifamily, Denver. $1.8M.
Income: $186K gross annually. $58K expenses. About $128K NOI.
Leases: Eight units renew 2026-2027. Unit 4 pays $1,200 when market is $1,550. That tenant's been there eight years. Owner likes keeping good tenants—fair enough. Two units vacant six months.
Capital: Roof needs replacing in 3-5 years. Budget $65K. HVAC is original, 15 years old. Parking lot needs seal coat.
Risks: The valuation presents a significant cap rate compression relative to comparable market transactions, with properties in this submarket currently trading at 4.2% while this memorandum projects a stabilized cap rate of 5.1%—a 90-basis-point gap that warrants structural investigation rather than assumption-based analysis….
Questions: (1) Why is this deal trading below market cap rates if it's so strong? (2) What's the actual plan for those two vacant units? (3) Is the roof replacement being prorated in the purchase price, or does my client eat it?
You've got your roadmap. Ask these questions. Get real answers. Then decide if your client should move forward.
Drill Deeper
After the summary, ask follow-ups:
"Calculate the cash-on-cash return assuming 20% down at 6.5% over 20 years. What's the monthly debt service and annual cash flow after debt service?"
Or:
"Flag every optimistic assumption. The memo projects 95% occupancy by year two. Based on the neighborhood data, is that realistic?"
Or (if lease abstracts exist):
"List every lease expiring in the next three years. Tenant name, current rent, expiration date, renewal terms. Highlight below-market rents."
Where AI Fails
AI organizes data. AI doesn't judge it. Here's what you still do:
Verify the math. AI can misread numbers or miscalculate cap rates. Don't trust it.
Read page one and the risk section yourself. AI might miss a footnote that changes everything.
Know your market. AI doesn't know if that neighborhood is actually gentrifying or if the seller is selling fantasy. You do.
Call your broker or attorney on legal terms. AI isn't qualified.
The Difference
Most agents never read the full OM. They wing it. The ones who actually understand the deal ask better questions and close better deals. Using AI to speed up the reading just means you're the agent in the room who knows what's happening.
Spend 15 minutes with this prompt on your next OM. You'll feel the difference.
