How Real Estate Agents Are Actually Using AI

Strategy

How Real Estate Agents Are Actually Using AI

Separate reported AI adoption from the smaller set of uses that remove recurring work from an agent’s week.

10 min read

The National Association of REALTORS®’ 2025 Technology Survey found 41% of respondents using AI or generative AI; in a separate impact question, 46% reported neutral or no noticeable business impact. Those figures frame how real estate agents use AI: adoption is visible, effect is uneven. A faster output can still leave the surrounding job intact.

The gap looks less mysterious when the unit of work is clear. Opening an AI tool counts as adoption.

Producing a listing-description draft counts as use. Neither one says whether the agent stopped doing the repeated setup, fact gathering, review, formatting, filing, or follow-through around that draft.

This article reports what the available surveys measured, then separates a quicker task from work removed from the week. It does not turn a self-reported use into a productivity result the survey never claimed.

What do the adoption and effect numbers measure?

The NAR figures come from different questions in the same survey. The National Association of REALTORS®’ 2025 Technology Survey reported that 41% of respondents currently used AI or generative AI as an emerging technology. In its separate frequency question, the National Association of REALTORS® reported in 2025 that 20% used AI daily, 22% weekly, 27% a few times a month, and 32% had not actively tried it for business.

Those frequency shares describe how often respondents said they used AI. They do not measure how much work disappeared.

The impact question asked for a business judgment. The National Association of REALTORS®’ 2025 Technology Survey found 17% reporting a significantly positive impact, 33% a moderately positive impact, 46% neutral or no noticeable impact, 2% moderately negative, and 2% significantly negative.

The published survey does not tie each impact answer to a specific task, workflow, transaction count, revenue change, or hour saved. “No noticeable impact” therefore means exactly what the respondent reported. It does not establish that the tool produced no useful draft.

Which AI uses are agents reporting?

The table uses two approved sources. NAR surveyed a random sample of active members about technology. Inman Intel surveyed agents about how they used AI and, for several complex tasks, published separate shares for paid reasoning-model users and free-tier or other users.

The rows overlap and the percentages should not be added. “AI-generated content” is a broad NAR technology category, while the Inman Intel rows ask about specific text tasks. The last column is Avenue Growth’s workflow analysis, not a time-savings result reported by either survey.

Reported use Share reporting it What part of a week it can remove
AI-generated content, including listing descriptions National Association of REALTORS®, 2025: 46% of respondents The blank page and some sentence-level drafting; source collection, fact checking, MLS review, and approval remain
Property-description text Inman Intel, 2025: 69% of agent respondents in its August survey A first description draft; property verification, edits, required brokerage language, and final entry remain
Social media or marketing text Inman Intel, 2025: 57% of agent respondents in its August survey A caption or first version; topic choice, local source material, visual work, platform adaptation, approval, and posting remain
Summarizing contracts or other documents Inman Intel, 2025: 52% of paid reasoning-model users and 10% of free-tier or other users An orientation pass through supplied text; the agent’s source review and broker or qualified legal guidance remain
Analyzing or summarizing market data Inman Intel, 2025: 59% of paid reasoning-model users and 22% of free-tier or other users Initial organization and summary of supplied data; source checks, local interpretation, and client judgment remain
Extracting data from property photos Inman Intel, 2025: 29% of paid reasoning-model users and 5% of free-tier or other users A first inventory of visible details; the agent still verifies every feature against approved property sources
Chatbots for lead capture or client communication National Association of REALTORS®, 2025: 7% of respondents Initial acknowledgment or field collection when brokerage rules permit; the agent still owns the conversation and factual answer 
AI creates an output
        ↓
Agent supplies missing context, checks facts, edits, formats, and delivers it
        ↓
The draft moved faster; the surrounding job stayed

The dominant pattern is text. Inman Intel reported in 2025 that property-description text and social or marketing text were the two largest agent uses in its August survey, at 69% and 57%. Each produces something visible quickly, which makes it an easy place to begin.

The more complex uses show a different split. Inman Intel reported in 2025 that paid reasoning-model users used document summary, market-data analysis, and property-photo extraction at much higher rates than free-tier or other users. Inman Intel also cautioned in 2025 that willingness to pay may identify agents who already get more value from AI, so the comparison does not prove that paying causes the productivity difference.

What can these real estate AI statistics not tell us?

Neither survey followed an agent’s work minute by minute. The responses show which tools and tasks agents selected, how often they said they used AI, and how they judged its business impact. They do not show the before-and-after duration of a listing description, social post, document review, or market summary.

The use labels also hide different operating patterns. Two agents can both report using AI for social media text.

One may request a caption once a month. The other may supply local sources to a standing workflow that returns a week of platform-specific drafts in a stored voice.

Both answers count as use. Only the second description tells us whether repeated work changed.

The survey questions also use different frames. NAR’s current-emerging-technology question, its AI-frequency question, and its AI-impact question appear separately in the report. Treating one percentage as a subset of another would add a relationship the published tables do not establish.

The same caution applies to Inman Intel’s paid-versus-free comparison. Higher reported use among paid-model users can reflect the model, the agent’s existing commitment, the complexity of their work, or several factors together. Inman Intel names that limitation in its 2025 analysis.

These boundaries make the evidence more useful. The surveys establish adoption, reported tasks, and perceived effect. The workflow around each task explains why those three measures can move in different directions.

Which AI uses move a minute, and which move a week?

A one-off draft moves a minute when the agent still performs every step around it. The listing description appears faster, then the agent checks each property fact, removes invented language, applies MLS and brokerage rules, and starts with a blank chat on the next listing.

A social caption works the same way. A model can produce three versions in one sitting. The agent still has to choose a useful local subject, supply the source, restore their voice, make the visual, decide where each version belongs, and post it.

Those are useful gains. They can reduce composition time and make an avoided task easier to start. They remain hard to see at the business level because the calendar, approval queue, client conversation, and publishing step still belong to the same person.

A use begins to move the week when it removes a repeated handoff. The system already has the job description, trusted inputs, voice rules, output shape, and recent work. It returns the needed set in the right format and preserves enough state for the next run.

That distinction is the center of real estate AI software. Model intelligence matters. Standing context and a repeatable job determine whether the agent receives an interesting answer or less work.

Why is adoption without business effect the expected result?

Adoption measures access and activity. Business effect arrives after a recurring responsibility changes shape.

First comes the setup tax. A general chat does not begin with the agent’s market, voice, brokerage constraints, current listing facts, and last approved output on file.

The agent pastes that context again or accepts a draft that sounds generic. ChatGPT for Real Estate shows where plain ChatGPT is enough and where that repeated setup starts to cost the task.

Then comes the checking tax. A confident property detail, market number, or contractual summary still needs comparison with the source.

The higher the stakes, the less of that review can be treated as optional. Faster generation can create more material to inspect.

Finally, output is easy to count while removed work is easy to miss. Ten captions in a document look productive. If none has a verified local source, approved visual, platform version, or place on the calendar, the agent gained inventory and kept the job.

The NAR impact result fits that sequence. A first draft can feel useful without changing revenue, client response, or the hours that define a week. The result becomes noticeable only when the repeated work around the draft shrinks too.

How should an agent judge their own AI use?

List the AI-assisted work from the previous week. For each item, write down what the model produced and what you still did before the task was complete.

Use four questions:

  1. What context did I have to paste again?
  2. Which facts or claims needed source checks?
  3. Which formatting, approval, filing, posting, or sending step remained?
  4. Did this output remove a repeated step next week, or only finish today’s first draft?

The answers reveal the difference between a quick interaction and an operating change. Where Your Week Goes helps identify the repeated job worth measuring, rather than judging AI by the quality of its most impressive single answer.

An agent using AI for listing copy may find that the first draft is no longer the bottleneck. The bottleneck may be gathering facts and approvals. An agent using it for social posts may find that publishing consistency, not writing speed, controls the result.

That is not a reason to discard the faster draft. It is a reason to name the rest of the job.

What job turns AI adoption into removed work?

The job is turning a faster first draft into removed recurring work. It needs standing instructions, current context, defined outputs, and a review boundary the agent can trust.

Avenue Growth is $89 a month, with the first 14 days free. Its Content Strategist is live: it plans content and drafts platform-specific posts in the agent’s voice for the agent to review and post. Hire it for the repeated content job, not for a single clever caption.

The Engagement Manager is the planned employee for prioritizing past-client outreach and preparing message drafts. It remains deferred post-MVP. Avenue Growth prepares drafts; the agent reads, edits, and decides what to send or post.

The useful result is not a larger pile of AI output. It is a smaller recurring job on your week.

Sources: National Association of REALTORS®, 2025 REALTORS® Technology Survey; Inman Intel, “Decoding Real Estate’s AI Liftoff” (2025); Avenue Growth audience and product canon.