AI for Real Estate

The book

Most of the AI advice circulating in real estate right now was written by people who have never sat across from a seller who thinks their home is worth $75,000 more than the comps say. AI for Real Estate starts from a different place — an honest accounting of where AI actually earns its keep in a working agent's week, and where it quietly wastes your time. Marcus Hale works through twelve specific workflows, from MLS data analysis to open house follow-up, with the actual prompts and the anonymized listing examples to go with them. The skepticism is not a caveat; it runs through the whole book.

What you'll learn

• How to write listing descriptions that sound like you wrote them, not like a tool trained on generic property copy
• A repeatable workflow for turning raw MLS data into CMA writeups that are accurate, defensible, and faster to produce
• How to run email follow-up at volume without your responses reading like a broadcast — including lead qualification scripts that hold up in real conversations
• Which parts of a pricing conversation with a seller AI can help you prepare for, and which parts it cannot substitute for your judgment
• What you should never paste into a public AI tool, and how to keep your compliance exposure manageable
• A 30-day rollout plan sized for an agent who is already at capacity and cannot afford to treat this as a side project

Who it's for

This is for the working agent already carrying active listings, a lead pipeline, and more client emails than any one person should write alone. You do not need a technology background or a new software stack. You need a clear-eyed view of which AI tools hold up in a real production environment and a practical way to put them to use this week.