Let AI Draft the Follow-Up. Keep the Judgment.

Start with a familiar task, not an autonomous agent

A 2026 NAR technology report says that among agents who use AI, common uses include writing emails and follow-ups. The report also says agents prioritize tools that help save time and improve client experience. These are reported uses and priorities, not proof that AI follow-up saves time or improves outcomes for every team.

That makes a supervised drafting pilot a more grounded starting point than letting an agent send messages on its own. Give the tool a narrow job: organize supplied notes into a clear draft, identify missing details, and suggest a next step for the human to consider. The agent remains responsible for deciding what is appropriate, checking facts, and communicating with the client.

Design the workflow around review

Choose one repeatable moment, such as a post-consultation recap or a check-in after a showing. Use a brokerage-approved tool and a template that specifies the audience, purpose, tone, and information the message must include. Provide only the minimum information needed; avoid entering confidential client details or transaction documents into an unapproved system.

Ask AI for a draft, not a decision. For example, have it summarize the agent’s approved notes, list any unanswered questions, and draft a concise message without inventing commitments, property facts, or market claims. Before sending, the agent checks names, dates, facts, tone, privacy, and whether the proposed next step reflects the actual conversation. If the draft is wrong or uncertain, revise it or start over.

Treat risk management as part of the test

NIST describes its AI Risk Management Framework as voluntary guidance for managing risks associated with AI and incorporating trustworthiness into the design, development, use, and evaluation of AI systems. It is not a brokerage-specific recipe or a certification. For a small pilot, its emphasis on evaluating use and risk supports a practical habit: decide in advance what information may be used, who reviews the output, and what happens when the tool produces an unsupported statement.

Set a simple stop rule. Do not send a draft that includes an unverified fact, exposes information the team did not authorize for the tool, or makes a client-facing recommendation the agent has not independently assessed. Keep a record of whether the message was edited, rejected, or sent after review. This is a proposed operating control, not a claim that the framework mandates these exact steps.

Run a bounded, measurable pilot

For two weeks, test the workflow with one agent or a small team and one message type. Compare a sample of AI-assisted drafts with the team’s usual process. Record, for each message, drafting and review time; whether the draft needed factual correction; whether any required detail was missing; and whether the agent sent, revised, or discarded it. Do not include sensitive client information in the measurement log.

Agree on success criteria before starting. For example: no uncorrected factual errors in sent messages, no increase in missed required details, and review time low enough that the workflow is usable. The team can choose its own acceptable time threshold. If quality slips or review takes longer than ordinary drafting, stop or adjust the template. A short pilot can inform a local process decision; it cannot establish guaranteed savings or business results.

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