How AI Search Is Recommending LLC Formation Services: Monthly Trends

Executive Summary

Northwest Registered Agent strengthened its hold on the LLC formation services category in September 2026, reaching 63.6% valid recommendation coverage. The 5.5-point gain from August's 58.1% was the sharpest upward movement in the category this month, though it stayed within the benchmark's normal month-to-month range for this brand. The gap to second-place ZenBusiness widened to 5.9 points in September, up from 5.2 points in August and 1.3 points in July.

The category was otherwise quiet. ZenBusiness rose 4.8 points to 57.7% coverage (from 52.9% in August), the second-largest movement of the month, while LegalZoom edged up 1.0 point to 46.8%. No brand moved beyond its normal month-to-month range this month, and the benchmark flagged no notable risers or decliners. Movement was concentrated in the top tier, where the three leading brands all strengthened their positions relative to July.

Across the full July-to-September series, Northwest Registered Agent has widened its coverage lead over both Bizee (Incfile) and LegalZoom in every tracked month, while the gap between Northwest Registered Agent and Rocket Lawyer has grown from 44.8 points to 52.4 points. The category structure remains a top tier of four brands above 44% coverage and a long tail below 12%.

Each monthly run begins with 800 prompt-surface observations (519 unique questions in September 2026) across the benchmark's defined AI/search surface universe. Of those, 800 mentioned a tracked brand or competitor; 597 were relevant and 203 were irrelevant. The public metrics use the 357 qualified observations that survive both qualification stages. For context, July 2026 began with 800 prompts (455 unique questions) with 315 qualified observations, and August 2026 began with 800 prompts (516 unique questions) with 384 qualified observations.

Key Findings

Benchmark Context

The report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set.

August 2026, which sits between these two months in the series, had 384 qualified observations. The September decline to 357 changes the denominator behind every brand's coverage rate, a factor referenced in the brand-level sections below.

Benchmark-Level Metrics

AI Recommendation Trend

The leader strengthened while the top tier held its shape

Northwest Registered Agent extended its lead in September, moving to 63.6% coverage from 59.7% in July and 58.1% in August. ZenBusiness and LegalZoom also sit above 46% coverage, forming a top tier of three brands that AI systems recommend most consistently. Bizee (Incfile) rounds out a four-brand upper cluster at 45.9%, though its gap to the leader has widened every month since July.

No brand moved beyond the benchmark's normal month-to-month variation in September. The month's shifts came from the combination of several smaller movements, led by Northwest Registered Agent's 3.9-point gain from July and the modest recoveries of Bizee (Incfile), LegalZoom, and ZenBusiness from their August dips. The category's structural divide between the top four brands and the rest of the field persists.

What Changed This Month

Northwest Registered Agent: strengthening presence drove the leader's gain

Coverage rose to 63.6% in September, up 5.5 points from August's 58.1% and 3.9 points from July's 59.7%. Raw mention presence rose from 82.5% in July to 92.4% in September, a 9.9-point gain across the series.

The placement mix tells a more nuanced story. Top-three rate held exactly flat at 54.9% across the full series, while rank-one rate rose from 22.9% to 28.0% (72 of 315 qualified observations in July to 100 of 357 in September). The brand is being named first more often without losing its position inside top-three lists.

The distinction matters: Northwest Registered Agent gained mention presence and rank-one placement while holding its top-three rate steady, a combination that pushed overall coverage to its highest level in the tracked series.

Highest-priority diagnostic: which prompt categories are driving the rank-one gains, and whether the September shift reflects changes in AI surface behavior or in the source material those systems draw from.

Bizee (Incfile): coverage dipped from July but stabilized against August

Coverage settled at 45.9% in September, down 5.8 points from July's 51.7% but up 1.9 points from August's 44.0%. Raw mention presence fell 11.0 points across the series, from 71.8% in July to 60.8% in September, yet valid recommendation count held at 164 in September, essentially flat with July's 163.

The placement data shows a counter-movement: top-three rate eased 1.2 points to 32.8% from July, but rank-one rate rose from 2.2% to 4.8% (7 of 315 observations in July to 17 of 357 in September). Bizee (Incfile) is appearing in fewer AI answers overall but is being named first slightly more often within the answers where it does appear.

The distinction to notice is between presence and recommendation. Bizee (Incfile) lost ground in how often it is mentioned at all, but retained a stable core of recommendation placements inside the answers that do include it.

Highest-priority diagnostic: which prompt types no longer mention Bizee (Incfile), and which competitors are absorbing those lost appearances.

ZenBusiness: recovered from August, though rank-one placements lag July

Coverage reached 57.7% in September, up 4.8 points from August's 52.9% and nearly matching July's 58.4%. Raw mention presence rose from 82.2% to 87.4% across the series.

The weaker signal sits in rank-one placement. ZenBusiness's rank-one rate fell from 30.5% in July to 23.0% in September, a 7.5-point decline across the series (96 of 315 observations to 82 of 357). Top-three rate also eased 3.7 points to 49.6% across the series.

ZenBusiness remains a strong second-place brand with wide presence across AI surfaces, but it is being named first less often than it was in July. The distinction between overall coverage and first-position wins is central to interpreting this brand's September position.

Highest-priority diagnostic: which prompts previously returned ZenBusiness first and now return another brand.

LegalZoom: stable coverage with a notable top-three decline

Coverage moved to 46.8% in September, down 5.3 points from July's 52.1% but up 1.0 point from August's 45.8%. Raw mention presence held relatively steady at 87.7%, down 2.5 points from July.

The sharper movement is in top-three placements: LegalZoom's top-three rate fell from 26.4% in July to 17.9% in September, an 8.5-point decline across the series (83 of 315 observations to 64 of 357). Rank-one rate also eased from 5.7% to 2.8%.

LegalZoom remains widely present in AI answers, but it is being positioned inside the top three far less often than it was two months ago. The brand is visible without being recommended as prominently.

Highest-priority diagnostic: which surfaces or prompt types are dropping LegalZoom out of top-three shortlists, and which brands are capturing those slots.

Rocket Lawyer: presence declined from July

Coverage moved to 11.2% in September, up 1.8 points from August's 9.4% but down 3.7 points from July's 14.9%. Raw mention presence fell from 25.1% in July to 18.8% in September, a 6.3-point decline across the series (79 of 315 observations to 67 of 357).

Valid recommendation count slipped from 47 to 40 across the series. Top-three rate eased from 5.4% to 3.9%, and rank-one rate from 1.6% to 0.8%. Net sentiment stayed positive at roughly 0.6, meaning the tone of answers that do mention Rocket Lawyer has not soured.

The decline is concentrated in how often the brand appears at all, not in how it is described. Rocket Lawyer's small observation counts mean its percentage movements should be treated as directional rather than precise.

Highest-priority diagnostic: which prompt categories reduced their mentions of Rocket Lawyer, and what changed in the source material for those queries.

Buyer-Intent Interpretation

In September 2026, all 357 qualified observations fell into the Brand Recommendation class. The benchmark's current prompt set can answer "which service should I choose?" but cannot yet answer pricing, value, or head-to-head comparison questions. The public metrics describe the recommendation landscape only; they do not capture how AI systems characterize cost differences or trade-offs between brands, and they cannot reveal whether a brand wins on price, features, or reputation.

Brand Opportunity Summary

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations capturing the query, the AI surface, the recommendation outcome, the rank, sentiment, and citations where exposed. Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence in the current dataset is not treated as proof of causation.

About This Benchmark

This report is part of the LLM Authority Index AI Market Discovery research program.

• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

Brands like Firstbase, Swyft Filings, and Rocket Lawyer have small qualified observation counts, so their percentages move on a handful of prompts; treat their figures as directional rather than precise. The public metrics use the qualified observation count (357 in September), not the raw prompt collection (800), so all percentages reflect the qualified set. Month-over-month movement identifies where attention is warranted; it does not by itself establish the cause of that movement.

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

Beneath the aggregate percentages sit the questions that matter for strategy: which high-intent prompts are won and lost, which competitor takes the recommendation when a brand loses, what attributes AI systems associate with each option, and which external sources shape those answers. The benchmark shows the outcome; it does not reveal the mechanism.

A company-specific AI visibility audit maps prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It answers the "why" behind the movement and identifies the specific queries and sources where intervention would change the recommendation outcome.

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