Download the Hitchhiker's Guide to AI for CRE here
What This Guide Is
AI is entering commercial real estate workflows whether you invited it or not — OMs, lease abstractions, investor memos, financial models. But most resources explaining how it works are either written for engineers or buried in vendor marketing.
This guide is different. It's a plain-language introduction to how AI actually works, written specifically for CRE professionals, explained through the workflows you run every day.
No engineering background required. No hype. Just the mechanics that matter.
Built on Real Research and Real Implementations
This guide isn't an opinion piece. It's grounded in seven years of AI and asset pricing research conducted at Harvard and MIT, combined with 5,000+ hours spent implementing this technology for some of the most sophisticated real estate institutions in the world.
That combination — rigorous academic research and hands-on deployment at institutional scale — is what makes this guide different from anything else in the market. We know how these models behave in theory. We've also watched them succeed and fail on real deals, with real capital at stake.
What's in this guide is what we've learned from both.
What You'll Learn
The guide covers the core concepts every CRE professional should understand right now:
- How LLMs actually work — and why that changes how you should interpret their output
- Tokens and context windows — the hidden limits that can cause AI to silently drop data from your rent rolls and documents without warning
- Hallucinations — what they are, why they're particularly dangerous in CRE, and how to protect yourself on a live deal
- Prompting — how to get dramatically better results by changing how you talk to AI
- Where AI works and where it fails — a straight assessment across OMs, lease abstraction, financial modeling, market research, and investor communications
- What shifted in late 2025 — why purpose-built tools can now produce institutional-grade Excel models with full DCF, waterfall, and debt stack structures in minutes
Who It's For
Fund managers evaluating AI platforms for their investment teams. Analysts trying to move faster without sacrificing accuracy on numbers that matter. Principals at boutique shops separating legitimate tools from vendor noise. Brokers watching AI-generated materials reshape their market.
The common thread: you make decisions where the numbers have to be right, and you want to understand what the technology is actually doing before you trust it.
Why It Matters
A model that silently drops half your rent roll or fabricates a comp looks exactly the same as one that gets it right — the output is confident either way. The professionals who navigate AI well won't be the ones who adopt it fastest. They'll be the ones who understand it well enough to know when to trust it, when to verify it, and when to push back.
This guide gives you that foundation.
