How AI Search Is Recommending Expense Management Software: Monthly Trends

Executive Summary

Ramp remains the category leader by valid recommendation coverage in September 2026, but the pattern across the top of the category is one of sustained compression. Ramp's coverage stands at 60.9%, down 8.0 points from 68.9% in July 2026, a decline the benchmark classifies as significant. The gap between Ramp and second-place Brex narrowed slightly, while the distance between the leader and the broader field has tightened as several large brands lost recommendation share.

Brex recorded the largest upward movement of the month, adding 3.1 points to reach 48.9% coverage in September 2026, recovering from a sharp August decline. That rebound moved Brex past Expensify into second place. Expensify recorded the sharpest decline of the month, falling 10.6 points from 49.1% in August 2026 to 38.5% in September 2026, a significant drop that pushed it from second to fourth position behind SAP Concur.

Across the July-to-September series, four brands are classified as significant decliners: Ramp, Brex, Expensify, and Rydoo, with no brand classified as a significant riser. The category result reflects significant movement at multiple positions rather than a single dominant shift.

This benchmark's public metrics are calculated from the qualified observations that survive the benchmark's eligibility checks: 473 qualified observations in July 2026, 511 in August 2026, and 468 in September 2026, spanning all six tracked AI/search surface families (ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode). Brand-level rates in this report are calculated within these qualified counts.

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.

The qualified counts above define the denominator for every brand-level rate in this report. August 2026 sat between the baseline and current months with 511 qualified observations; that larger intermediate set is noted for context but does not appear as a comparison column. The following category-level metrics summarize how the qualified set behaved across the full series.

Benchmark-Level Metrics

AI Recommendation Trend

The Leader Held Its Position, But Significant Declines Reshaped the Ranks Behind It

Ramp kept first place in September 2026, but the composition of the rankings behind it shifted materially. Expensify's significant decline and Brex's partial recovery moved Brex back into second and pushed Expensify to fourth. The benchmark classifies four brands as significant decliners across the July-to-September series and no brand as a significant riser; the net result is a category where the leader retained its position while the distance among the top four narrowed.

What Changed This Month

Ramp

Ramp's valid recommendation coverage fell from 68.9% in July 2026 to 60.9% in September 2026, a decline of 8.0 points that the benchmark classifies as significant. The move from the prior month was smaller: Ramp rose 1.4 points from 59.5% in August 2026, so the significant classification reflects the full baseline-to-current movement.

Ramp's top-three recommendation rate dropped from 54.5% in July 2026 to 47.2% in September 2026, down 7.3 points. Its rank-one rate declined from 30.4% to 29.5%, down 0.9 points. Raw mention presence rose from 87.5% to 89.5%, up 2.0 points.

The distinction that matters: Ramp remains the most visible brand in the category, and its raw presence actually increased over the series. The coverage decline is therefore concentrated in how often Ramp is recommended within answers, not in how often it appears.

Highest-priority diagnostic: Which prompt types or AI surfaces accounted for the largest share of Ramp's coverage decline, and which brand picked up those recommendation slots?

Brex

Brex's valid recommendation coverage fell from 56.7% in July 2026 to 48.9% in September 2026, down 7.8 points and classified as a significant decline. But the sharper story is the recovery from the prior month: Brex rose 3.1 points from 45.8% in August 2026, regaining second place.

Brex's top-three recommendation rate declined from 37.8% in July 2026 to 31.6% in September 2026, down 6.2 points. Its rank-one rate fell from 8.2% to 3.0%, down 5.2 points. Raw mention presence declined from 72.7% to 69.9%, down 2.8 points.

The distinction to notice: Brex's coverage partially recovered in September 2026 after a sharp August drop, but its rank-one rate continued to fall and now sits at just 14 rank-one placements out of 468 observations — the brand is reappearing in more recommendation answers without regaining the top placement it held in July 2026.

Highest-priority diagnostic: Which competitor is taking the first-position recommendation when Brex appears but does not rank first, and which surfaces drive that pattern?

Expensify

Expensify recorded the sharpest decline of September 2026: valid recommendation coverage fell 10.6 points from 49.1% in August 2026 to 38.5% in September 2026, a move the benchmark classifies as significant. Across the full series, coverage fell 6.7 points from 45.2% in July 2026, also significant.

Expensify's raw mention presence declined from 57.1% in July 2026 to 54.1% in September 2026, down 3.0 points. Its top-three rate fell from 24.1% to 20.9%, down 3.2 points, and its rank-one rate declined from 7.8% to 7.5%.

The distinction that matters: Expensify's August gain to 49.1% coverage was reversed in September, with rank-one placements falling to 35. The decline spans presence, top-three, and rank-one rates, indicating a broad reduction in how often Expensify is recommended rather than a shift confined to one placement tier.

Highest-priority diagnostic: Which high-intent prompts produced Expensify's August rank-one gains, and did those same prompts stop recommending the brand in September?

Rydoo

Rydoo's valid recommendation coverage fell from 5.5% in July 2026 to 2.6% in September 2026, down 2.9 points and classified as a significant decline. The brand's valid recommendation count dropped from 26 observations in July 2026 to only 12 in September 2026.

Rydoo's raw mention presence fell from 7.0% to 4.3% over the same period, down 2.7 points. It recorded zero rank-one placements in both months, and its top-three rate moved from 0.4% to 0.6%, an increase of 0.2 points. Net sentiment among its mentions declined from 0.8 to 0.6.

The distinction to notice: Rydoo operates at very small observation counts, so its percentage movements rest on small absolute numbers. The trend across the July-to-September series is a steady loss of presence, with the brand appearing in fewer AI answers each month.

Highest-priority diagnostic: Which specific prompts still mention Rydoo at all, and which surfaces dropped the brand entirely over the series?

Zoho Inventory

Zoho Inventory recorded a notable recovery in September 2026: valid recommendation coverage rose 6.8 points from 0.0% in August 2026 to 6.8% in September 2026, a move the benchmark classifies as significant. Across the full series, coverage declined 0.4 points from 7.2% in July 2026.

Zoho Inventory's raw mention presence rose from 7.6% in July 2026 to 8.1% in September 2026, up 0.5 points. Its rank-one rate moved from 0.6% to 0.9%, and its top-three rate fell from 2.8% to 2.1%. The brand recorded 32 valid recommendations in September 2026.

The distinction to notice: Zoho Inventory fell to zero coverage in August 2026 when it dropped from the tracked-company list, then returned in September 2026 with coverage close to its July level. This pattern is consistent with a tracking-list change rather than a real brand-level shift in recommendation behavior.

Highest-priority diagnostic: Was Zoho Inventory's August absence a tracking artifact, and does its September coverage reflect a genuine return to AI recommendation answers?

Buyer-Intent Interpretation

The qualified observations in September 2026 all fell into the brand recommendation class; the pricing and multi-brand comparison clusters recorded zero observations in each of the three tracked months. The public benchmark therefore measures which brands AI systems recommend, but it does not yet capture how AI systems answer pricing questions or structured head-to-head comparisons. Those commercial questions remain outside the current benchmark's reach.

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 (query, surface, recommendation outcome, rank, sentiment, and citations where exposed). Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically 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

• Small-count movement: brands like Rydoo, Airbase, and Emburse have low observation counts; their percentage movements rest on small absolute numbers and should be read with that context in mind.
• Qualified denominator: brand-level rates are calculated within the qualified benchmark set (468 observations in September 2026), not the larger 800-prompt raw collection universe.
• Directional analysis: month-over-month movement identifies changes worth investigating; it does not by itself establish the cause of those changes.

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 a brand wins, 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 surfaces the what. It does not yet reveal the why behind an 8.0-point coverage drop at the leader or a 10.6-point swing at a former second-place brand.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. For a category where four brands recorded significant declines across the series, that level of detail is the difference between reacting to a number and understanding the shift.

Request an AI visibility audit