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One-page team boundary

Write the AI policy people can use mid-task.

A policy should answer three questions fast: Can I put this data in? Can AI make this decision? Who reviews the output before it reaches a client or system?

Practical guideReviewed August 20, 2026

The policy blocks.

  1. 01

    Allowed work

    Name approved tasks, accounts, and source types. Everything else starts as ask-first.

  2. 02

    Data boundary

    List information that never enters an unapproved model or account.

  3. 03

    Human-only decisions

    Reserve representation, pricing, legal, compliance, send, publish, and system-write decisions.

  4. 04

    Verification + disclosure

    Require source comparison, misleading-output checks, and clear disclosure where appropriate.

  5. 05

    Records + incidents

    Save prompts and approvals for material work; stop, notify, contain, and document mistakes.

  6. 06

    Review cadence

    Name the policy owner and schedule review when tools, laws, brokerage rules, or use cases change.

Draft in plain language. Review locally.

One-page AI policy drafter

Draft a one-page internal AI-use policy for a real-estate team.

APPROVED USE CASES
[list]

APPROVED TOOLS / ACCOUNTS
[list]

FORBIDDEN DATA
[client, transaction, financial, identity, access, or confidential data]

REQUIRED HUMAN DECISIONS
[pricing, representation, legal, fair-housing, send, publish, record update, etc.]

APPROVAL OWNER AND ESCALATION CONTACT
[roles]

Write plain-language sections for purpose, allowed work, prohibited inputs/actions, verification, disclosure, records, incident response, and review cadence. Include five realistic examples of “allowed,” “ask first,” and “do not do.” Flag every legal or brokerage-specific item as LOCAL REVIEW REQUIRED.

Situation

Client email draft

An agent wants help summarizing an approved inspection note into a clearer email.

Useful output

Allowed only in an approved account with permitted source data; factual summary compared to the note; agent decides advice, wording, and send.

Completion receipt

Source note ID, prompt, draft, human corrections, approval owner, and sent-message record from the existing system.

Keep building the system.

30-day rollout

Put the policy inside a limited pilot.

Open standalone guide →

Use-case scorecard

Avoid starting with high-consequence work.

Open standalone guide →

Automation quality gates

Translate policy into technical pause points.

Open standalone guide →

Research sources

Check the current rules, capabilities, and source basis.

  1. 01NIST: AI Risk Management Framework Core ↗

    The Govern, Map, Measure, and Manage framework, including training, intended-use, human-oversight, testing, and documentation outcomes.

  2. 02NAR: Artificial Intelligence in Real Estate ↗

    NAR's current overview of AI use in real estate and policy priorities around privacy, Fair Housing, and copyrighted listing content.

  3. 03NAR: 2026 Code of Ethics ↗

    Current professional standards requiring a true picture in advertising and prohibiting misleading images and manipulations.

  4. 04HUD: Fair Housing guidance for digital advertising ↗

    Government guidance on Fair Housing risk in digital housing advertising and delivery.

Product access, limits, local listing rules, platform policies, and laws can change. Re-check the linked authority before important or public work.

Keep building

Put AI to work in your real estate business.

AI Acceleration: Real Estate is a private, self-directed curriculum for practical AI work across content, communication, lead follow-up, CRM, client research, operations, and relationship management. Build it. Review it. Keep what works.

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No ranking, revenue, closing, or time-saving promise. The classes teach the work and the review systems around it.