M/I Homes Appears in 20.6% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Mark HuntleyBy Mark HuntleyFounder and CEO
10 minutes read

Key Takeaways

  • M/I Homes was mentioned in 104 of 504 benchmark answers and recommended in 70, showing stronger presence than endorsement.
  • The main issue is the gap between being discussed and being affirmatively recommended, not negative sentiment.
  • Two low-severity annual closings claims need primary-source verification before any page edits or correction requests.
  • Priority work includes reviewing high-citation third-party pages, updating key website pages, and building content around national and Florida home-builder questions.

Answer Capsule

In November 2026, M/I Homes appeared in 104 of 504 AI answers included in the Home Builders benchmark (20.63%). It received 70 recommendations (13.89%), with 9 Top 3 placements and 4 first-place recommendations. A mention means the company appeared in an answer; a recommendation means the answer affirmatively endorsed it.

Our plan compares the company with its competitors, checks conflicting AI claims against reliable sources, and identifies website pages, third-party sources and buyer questions to address. The historical results show how the figures changed across available months. Different monthly samples limit those comparisons, and conflicting AI claims require verification before corrections are proposed.

Current AI visibility

Questions This Section Answers

  • How do M/I Homes mentions, recommendations and placements compare with its Home Builders peers?

M/I Homes recorded 104 mentions (20.63%) and 70 recommendations (13.89%) across 504 answers included in the benchmark. Top 3 placements numbered 9; first-place recommendations numbered 4. Framing among its mentions was 70 positive, 34 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Lennar

473

93.85%

328

65.08%

294

58.33%

45

8.93%

2

D.R. Horton

453

89.88%

316

62.70%

280

55.56%

227

45.04%

3

Toll Brothers

383

75.99%

304

60.32%

72

14.29%

28

5.56%

4

PulteGroup

369

73.21%

290

57.54%

245

48.61%

3

0.60%

5

Taylor Morrison

329

65.28%

273

54.17%

92

18.25%

58

11.51%

6

Meritage Homes

263

52.18%

216

42.86%

24

4.76%

1

0.20%

7

NVR (Ryan Homes)

248

49.21%

180

35.71%

6

1.19%

1

0.20%

8

KB Home

214

42.46%

152

30.16%

23

4.56%

4

0.79%

9

M/I Homes

104

20.63%

70

13.89%

9

1.79%

4

0.79%

10

Clayton Homes

29

5.75%

19

3.77%

2

0.40%

1

0.20%

M/I Homes is mentioned in roughly one in five answers and recommended in about one in seven, so the brand is present in the conversation but rarely the answer. Its recommendation reach is meaningful relative to its first-place showings, which means buyers hear the name without often hearing it named first.

The gap between mentions and recommendations is the practical issue. Being discussed is not the same as being endorsed, and the framing of those mentions is overwhelmingly positive or neutral, so the shortfall sits in affirmative recommendation rather than in negative sentiment. The agency would treat reach and endorsement as separate goals and track them separately.

What changed since last month

Questions This Section Answers

  • How did M/I Homes counts and coverage differ across the available monthly snapshots?

Metric

Jul 2026

Sep 2026

Oct 2026

Nov 2026

Mentions

82 / 523 (15.68%)

94 / 550 (17.09%)

84 / 533 (15.76%)

104 / 504 (20.63%)

Recommendations

55 / 523 (10.52%)

65 / 550 (11.82%)

59 / 533 (11.07%)

70 / 504 (13.89%)

Top 3 recommendations

10 / 523 (1.91%)

18 / 550 (3.27%)

19 / 533 (3.56%)

9 / 504 (1.79%)

#1 recommendations

2 / 523 (0.38%)

3 / 550 (0.55%)

3 / 533 (0.56%)

4 / 504 (0.79%)

Only months with verified results are shown. Monthly sample coverage is listed in Methodology.

From October 2026 to November 2026, M/I Homes' mention count rose from 84 to 104, while its recommendation count rose from 59 to 70. The recommendation rate was 11.07% and 13.89% respectively.

The November sample shows more mentions and more recommendations than October, and the recommendation rate moved up alongside them. Top-three showings fell back from the October level while first-place showings edged higher, so the position mix shifted even as overall presence grew.

These are separate monthly samples with different answer sets, so the movement describes what was recorded rather than a trend with a known cause. The agency would read the next few months together before treating any direction as established, and would avoid attributing the change to sample size or to its own work.

AI recommendation trend

Observed recommendation rate (%), Jul 2026 to Nov 2026

0%3.75%7.5%11.25%15%Jul 2026Sep 2026Oct 2026Nov 202610.52%Jul 2026: 10.52%11.82%Sep 2026: 11.82%11.07%Oct 2026: 11.07%13.89%Nov 2026: 13.89%
  • M/I Homes13.89%

Separate selected monthly samples. Missing points are unavailable, not zero. Provider/prompt equivalence is unverified; rate movement does not demonstrate causation.

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Step 1. Measure

Questions This Section Answers

  • What should the agency measure and verify first for M/I Homes?

AI answers contained 2 conflicting claims about M/I Homes: 0 critical, 0 high, 0 medium, 2 low. Of these, 0 were rated critical or high priority; the critical claims are included in that total. These ratings help prioritize fact-checking. They do not establish that a company or publisher made an error.

A visibility comparison against the larger builders would show where M/I Homes is discussed but not endorsed, giving the client a defensible order of work. Pairing that with a short list of claims to fact-check keeps effort focused on statements that could mislead a buyer.

The two recorded claims about annual closings are both low severity, and they may simply reflect different reporting years. The agency would build a scorecard that separates presence, endorsement and position, then attach each disputed claim to an owner and an evidence requirement before anyone drafts a correction.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about M/I Homes should be verified before proposed page edits?

Review topic

Severity

Recorded AI claim A

Recorded AI claim B

annual closings

low

8,921 closings (2025)

9,055 closings (2024)

annual closings

low

8,921 closings (2025)

9,055 closings (2024)

Both columns quote AI answers, not verified company facts. Resolve the entity, date and source before deciding whether a correction is warranted; different dates can explain an apparent conflict.

The disputed claims concern annual closings, and the two recorded figures carry different years. That difference may resolve the apparent conflict without any page change, so the first step is confirming which year each figure belongs to and what the company's own reporting says.

The agency would verify against current primary sources before proposing any edit, and would prepare a conditional page brief only if the verified facts differ from what the site states. Where the entity or date cannot be confirmed, the item stays out of the correction queue rather than being guessed at.

Step 3. Align the external narrative

Questions This Section Answers

  • Which cited third-party pages are relevant to fact review for M/I Homes?

Cited page selected for review

Citation appearances in all captured answers

Answers mentioning the company

Conflicting claims linked to this page

https://builderonline.com/builder-100/builder-100-list/2026/

177

27

2

https://builderonline.com/builder-100/builder-100-list/2025/

73

12

2

https://probuilder.com/top-200/article/55295081/the-2025-top-200-rankings

15

4

2

https://roselawgroupreporter.com/2025/01/the-most-trusted-builders-for-2025/

1

1

2

https://lifestoryresearch.com/2025-best-home-builder-ranking-review

19

2

1

https://treasurecoasthomespot.com/blog/best-home-builders-florida/

12

5

0

These pages were selected because they relate to the company in the captured answers. Their current contents still need checking before any correction request. A page linked to a conflicting claim is not necessarily its cause, and the same answer may contribute to more than one row.

The ranking and review pages cited alongside M/I Homes are sensible starting points for source review, though a citation does not show that a page shaped what an answer said. The agency would check each selected page's current contents and note where company facts appear, treating the ranking lists and the trust and regional review pages as separate review targets rather than one group.

Where a genuine discrepancy is confirmed against a primary source, the agency would prepare an evidence-backed correction request with supporting documentation. Pages tied to conflicting claims are not assumed to be their cause, and no-change decisions would be recorded as carefully as outreach. Ambiguous company matches would stay outside the correction queue.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed M/I Homes website pages should receive review briefs?

Company website page

Citation appearances in all captured answers

Benchmark answers citing the page

Recommending answers citing the page

https://mihomes.com/blog/best-home-builders

36

32

5

https://mihomes.com/blog/best-home-builders-in-texas

8

8

2

https://mihomes.com/blog/best-home-builders-in-florida

6

6

0

https://mihomes.com/blog/houston/best-home-builders-in-houston

6

6

3

https://mihomes.com/blog/raleigh/best-home-builders-in-raleigh-nc

3

3

3

https://mihomes.com/resources/faq

3

0

0

https://mihomes.com/blog/orlando/best-home-builders-in-orlando-fl

2

2

0

https://mihomes.com/new-homes/florida/tampa-bay-area/tampa

2

2

2

The company's website was cited 79 times across 19 distinct page addresses; the table shows 8 pages selected for review. Zeros in the answer columns mean no matching answers were recorded. A cited page is not automatically a page that accompanied a recommendation.

The company's own best-builders blog pages are cited far more often than its FAQ or community pages, which suggests the ranking-style content is doing most of the work. Several of those pages appear in answers that recommend the company, while others appear only in general mentions.

The agency would write page briefs that use approved facts and answer the buyer questions those pages already attract, checking existing coverage before proposing anything new. Briefs would distinguish pages that accompany recommendations from pages that merely get cited, so effort goes where it can plausibly influence endorsement.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for M/I Homes?

Question observed in the research

Benchmark answers to this question

Company mentions

Company recommendations

Who are the top 20 home builders in the US?

5

5

5

Who are the top home builders in Florida?

5

4

3

Who are the top 10 home builders in Florida?

4

3

3

Who are the top 20 national builders?

5

5

2

Who are the big national home builders?

5

3

2

Who are the top homebuilders in Houston?

6

3

2

What home builder has the best reputation?

4

2

2

What is the best house building company?

4

2

2

These are recorded answer observations, not search volume, verified demand, or proof of missing website content.

The recorded questions cluster around national and Florida top-builder lists, with Houston and reputation questions appearing as well. M/I Homes is mentioned in most of these answers but recommended in fewer, and the Florida and Houston questions are where local content could matter most.

The agency would turn these observations into buyer-question briefs, checking whether existing pages already answer them before proposing additions. These are recorded answer observations, not search volume, so the briefs would be validated against the client's own audience evidence before publication.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed M/I Homes work and judge completion?

Period

Deliverable

Completion criterion

Days 1–30

Baseline scorecard, scoped fact-review register and page/source shortlist

Each record has an owner, evidence requirement and review status

Days 31–60

Approved page briefs and justified publisher requests

Separate confirmed edits, no-change decisions, requests and responses

Days 61–90

Buyer-content briefs and a fresh scorecard

Record work completed separately from measured answer outcomes and comparability limits

The first month establishes the baseline scorecard, a scoped fact-review register and a shortlist of pages and sources, each with an owner and a review status. The second month produces approved page briefs and justified publisher requests, with confirmed edits, no-change decisions and responses logged separately.

The final month delivers buyer-content briefs and a fresh scorecard. Completed work would be reported separately from measured answer outcomes, and the comparability limits between monthly samples would be stated plainly so no one reads delivery as proof of improved visibility.

Methodology

Questions This Section Answers

  • How are M/I Homes answer metrics and citation populations defined?

This report covers 2026-11. The exact dates when the original AI answers were collected have not been verified. The visibility rates use 504 answers that met the benchmark's inclusion rules. A company is recommended only when the answer both endorses it and uses positive wording. Top 3 and first-place counts are part of those recommendations, not extra recommendations.

An answer can mention or recommend several companies, so company counts cannot be added to find the number of distinct answers. The net sentiment score is positive minus negative mentions, divided by all company mentions; it describes answer wording, not customer satisfaction.

The wider citation analysis covers 800 captured answers and 4455 appearances of cited URLs. Citation appearances across all captured answers differ from the number of benchmark answers citing a page and the number that also recommend a company. The current contents of cited pages and disputed company claims still need independent verification.

Monthly sample coverage:

Reporting month

Answers included

AI services covered

Services

Jul 2026

523

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Sep 2026

550

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Oct 2026

533

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

Nov 2026

504

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

August 2026 measured a different set of companies, so it is excluded from this comparison.

The answer samples differ between months. These comparisons show how the recorded results changed; they do not establish why they changed.

The monthly samples differ, so comparisons show how recorded results changed rather than why. A recommendation requires both an endorsement and positive wording, and top-three and first-place counts sit inside recommendations rather than adding to them.

Cited pages and disputed claims still need independent verification, and a citation does not establish that a source influenced an answer. Sentiment describes answer wording, not customer satisfaction.

Our first three priorities

First, verify the annual-closings claims against current primary sources and confirm the reporting year before deciding whether any page needs changing. Second, review the most-cited ranking pages and prepare evidence-backed requests only where a real discrepancy is confirmed.

Third, brief the best-builders and Florida pages around the buyer questions already observed, using approved facts and checking existing coverage first. Throughout, the agency would keep presence, endorsement and position as separate measures so progress is judged on the right one.

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Understanding AI search visibility.

AI search experiences create answers by pulling information from many places online and summarizing it into a single response.

What Is AI Citation Intelligence?
AI citation intelligence is the process of measuring where AI platforms source their information and how frequently a brand is mentioned or referenced in AI-generated responses. Because LLMs synthesize across multiple sources, the sites and brands that appear repeatedly tend to influence how a topic or company is framed. This practice focuses on identifying which sources shape AI outputs and tracking brand visibility across different AI systems.
What Is Citation Architecture?
Citation architecture describes the set of sources that consistently inform how AI systems talk about a brand, product, or topic. LLMs draw from websites, articles, forums, and public discussion, and the sources they rely on most often become the backbone of their answers. Building strong citation architecture means ensuring that accurate, credible, high authority sources are the ones most likely to shape the way AI tools summarize and recommend a brand.
What Is Generative Engine Optimization?
Generative engine optimization (GEO) is the practice of improving the chances that AI systems use and cite your brand or content when generating answers. While traditional SEO is centered on ranking pages in search results, GEO focuses on how LLMs retrieve, interpret, and combine information when responding to a question. The objective is to strengthen the content and sources AI systems rely on, so your brand is treated as a trusted reference in AI responses.
What Is AI Share of Voice?
AI share of voice tracks how often a brand appears in AI-generated answers compared with competitors in the same category. It reflects visibility across AI platforms such as ChatGPT, Gemini, Claude, and Perplexity. Monitoring AI share of voice helps organizations see whether AI systems consistently include and recommend their brand for key queries or whether competitor brands are showing up more often.

About The Author

Mark Huntley

Mark Huntley

Founder and CEO

Mark Huntley, J.D. is founder of CiteWorks Studio, a strategic advisory focused on visibility, authority, and recommendation presence in AI-shaped search environments. His work centers on embedding-level GEO, vector optimization, and cosine gap engineering — helping brands align their digital presence with the retrieval systems that increasingly shape discovery, interpretation, and choice.

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