2026 Brokerage AI Risk Survey: Read the Sample

In the 2026 brokerage AI risk survey, 75% of respondents from firms with 20 or fewer agents cited real estate compliance concerns. That finding rests on just 16 respondents, according to Delta Media’s August 26 analysis. The figures measure reported concern. They do not establish incidents, losses or demonstrated technology failures. Owners evaluating AI vendors can use the findings to frame questions, but should be cautious about treating them as benchmarks for their own firms.

What the Delta Media AI leadership survey measured

The survey year is not the collection date. Delta’s January 29 release says more than 100 broker-owners and senior managers responded in December 2025. The findings reflect those executives’ answers, not a direct survey of every agent. Delta sells brokerage technology, giving it a commercial interest in vendor-selection discussions.

Its April question summary distinguishes two measures: worry about whether AI has adequate safeguards against risk and liability, and specific challenges or concerns about integrating AI into business operations. Neither question, as summarized, establishes that a respondent experienced a breach, regulatory violation or financial loss.

The August analysis reports average worry scores out of 10: 6.50 in 2024, 5.80 in 2025 and 6.38 in 2026. The survey does not establish that agentic AI caused the rebound.

For decisions about housing AI and automation, concern can justify investigation without establishing that a particular product is unsafe.

Read brokerage-size comparisons with their respondent counts

The August release provides these selected comparisons. Each percentage is the share reporting a concern:

Assuming unweighted answers and the stated denominator, the smaller group’s 75% represents 12 people. One person changing an answer would move the share by 6.25 percentage points, compared with about 1.49 points in the larger group. These calculations illustrate sensitivity; they are not margins of error.

The release supplies no equivalent concern table for firms with 21–100 agents. Owners in that range should not interpolate a score between the two groups. The nearly equal training percentages also do not demonstrate equal training needs, spending or effectiveness.

What remains unresolved about the sample

We did not locate a complete public questionnaire-and-methodology package for 2024–2026 available by August 28. The reviewed question summaries and releases do not establish recruitment procedures, response rates, weighting or whether the same leaders participated each year. The annual averages therefore cannot demonstrate that individual executives changed their minds.

The sample descriptions also differ. January’s methodology puts 31% of respondents at firms with 20 or fewer agents; the February 11 leadership-survey release says 15%. Both describe December 2025 responses without explaining the difference. Before combining the releases, ask Delta whether the respondent sets differ or a figure needs correction.

This report uses the August subgroup counts for the August comparisons. A fuller assessment would require the exact questions and answer options, the number answering each question, and an explanation of how respondents entered the analysis. Those details would help determine whether apparent differences reflect selection, question design or differing experiences.

When using data and research reports for operating decisions, ask whether the evidence supports the proposed action. These percentages do not establish industrywide prevalence or isolate brokerage size as the cause of concern.

Turn the findings into AI vendor procurement questions

Use the concern categories to organize a demonstration and a written proposal. The following are editorial recommendations, not controls whose effectiveness Delta tested. NIST’s January 2023 AI Risk Management Framework 1.0 provides a voluntary basis for examining responsibilities, third-party dependencies, monitoring and incident response.

What does compliance support actually do?

Ask the vendor to demonstrate review and approval of a proposed listing advertisement. Which checks run, what information must the brokerage supply, and who approves publication? Request the scope and exclusions in writing; have brokerage counsel review legal obligations and contractual responsibility.

For a small office, price the human work too. If every output requires owner review, include that time when comparing offers.

Where does information go, and what can the system change?

Request a diagram showing which providers receive client and listing information, retention periods, and whether data may be used for model training. Separately, ask which connected records the system can read or alter and which actions require approval.

For a larger firm, ask the vendor to follow one record through the proposed integrations. A hypothetical test could involve correcting a listing detail and checking where that correction appears. Define the expected result before watching the demonstration.

What evidence will justify expansion?

Agree on a limited pilot, named reviewers and a record of errors, overrides and completed tasks. Compare total costs—including training, integration and review—with work completed to an agreed standard. Ask how the brokerage can suspend automated actions, preserve records and obtain help after an error.

For brokerage operating decisions, make the next purchase conditional on evidence from the workflow you plan to use. Require the proposal to specify who does the work, what the brokerage can inspect and how corrections will be handled.