Data as of Aug 25, 2026 · Based on 2,195 AI responses · See how Parse measures this
Corporate Cards & Spend Management
Parse
https://parse.gl
Ramp has taken the top spot in AI recommendations for corporate cards and spend management, overtaking longtime leader . The most notable trend is the rapid ascent of integrated expense management tools like and , which are now frequently cited alongside the fintech leaders.
| # | Brand | What AI says | Mention rate |
|---|---|---|---|
| 1 | Praised for automated spend controls, visibility, and stopping out-of-policy spending. | 71% | |
| 2 | A top contender for startups, offering high limits without personal guarantees. | 63% | |
| 3 | Surged in mentions for unlimited virtual cards and automated expense reporting. | 29% | |
| 4 | 28% | ||
| 5 | Cited for spend policies tied directly to HR and employee data. | 27% | |
| 6 | Gaining traction for powerful controls ideal for scaling international teams. | 25% | |
| 7 | An all-in-one platform combining cards, | 17% | |
| 8 | 12% | ||
| 9 | 11% | ||
| 10 | 11% | ||
| 11 | 11% | ||
| 12 | Recommended for developers needing to create virtual cards programmatically via its API. | 10% | |
| 13 | 10% | ||
| 14 | 9% | ||
| 15 | 9% | ||
| 16 | 8% | ||
| 17 | 8% | ||
| 18 | 8% | ||
| 19 | 8% | ||
| 20 | 8% | ||
| 21 | 6% | ||
| 22 | 6% | ||
| 23 | 6% | ||
| 24 | 6% | ||
| 25 | 6% |
Who wins on each AI
The same market, seen by two models.
Sources AI cited
ramp.com is the page AI reaches for most here, cited in 60% of analyzed answers.
Mention rate jumped from 4% in Oct 2025 to 30% by Mar 2026.
“Mentioned generally for financial tools.” → “Specifically recommended as 'BILL Spend & Expense (formerly Divvy)' for budget-based card controls.”
Rose from rank #11 to #6 overall between Oct 2025 and Mar 2026.
| Brand | ChatGPT Search | Google AI Mode | Comparison |
|---|---|---|---|
| 86% | 73% | ||
| 76% | 61% | ||
| 33% | 37% | ||
| 27% | 26% | ||
| 7% | 33% |
The two models disagree most about Airbase (ChatGPT #8, Google #25) and Payhawk (ChatGPT #21, Google #4).
Ramp has taken the top spot in AI recommendations for corporate cards and spend management, overtaking longtime leader Brex. The most notable trend is the rapid ascent of integrated expense management tools like Expensify and Payhawk, which are now frequently cited alongside the fintech leaders.
Across 2,195 AI responses, Ramp is mentioned most, named in 71% of them, followed by Brex (63%) and Expensify (29%).
Parse measures each brand's mention rate — the share of answers naming it — across 2,195 AI responses to this market's buyer questions. Answers are collected daily and the ranking is published weekly.
Brands enter the ranking when AI answers mention them. Parse collects answers daily and publishes the re-measured set weekly, so new brands appear as AI starts recommending them.
AI answers consistently name a core group of modern fintech platforms for general control and visibility. Early responses in late 2025 sometimes included a wider set of tools, but by 2026, ChatGPT and Google AI Overviews have converged on recommending Ramp,
Brex, and
Rippling as the top tier for this query.
AI answers consistently name a core group of modern fintech platforms for general control and visibility. Early responses in late 2025 sometimes included a wider set of tools, but by 2026, ChatGPT and Google AI Overviews have converged on recommending Ramp,
Brex, and
Rippling as the top tier for this query.
This prompt has been a tight race between Ramp and
Brex, with both consistently cited as the top two choices. is also a frequent recommendation, often positioned for companies who want to integrate spend with their existing HR stack. By early 2026, (via .com) also began appearing more frequently in responses.
This prompt has been a tight race between Ramp and
Brex, with both consistently cited as the top two choices.
Rippling is also a frequent recommendation, often positioned for companies who want to integrate spend with their existing HR stack. By early 2026,
Divvy (via
BILL.com) also began appearing more frequently in responses.