Citewake

Edition 2

Corporate cards: what AI recommends, Citewake Edition 2 (collected 29–30 Oct 2026)

United States. Ramp was the brand the four AIs recommended most often: in 86.0% of decision answers (90% interval 77.8–94.0), followed by Brex (77.3%) and Rho (26.1%). The AIs disagreed: Gemini recommended Ramp in 90.7% of its decision answers, Claude in 81.2%; the widest gap among the top 15 was Rho, 41.3 points between Claude and Perplexity. The figures come from 120 valid answers of 120 planned, to 30 questions asked once of each AI between 29 and 30 October 2026, which named 132 brands in all.

Europe — composite research panel. Pleo was the brand the four AIs recommended most often: in 42.6% of decision answers (90% interval 31.7–53.6), followed by Revolut Business (37.7%) and Spendesk (27.4%). The AIs disagreed: Claude recommended Pleo in 52.8% of its decision answers, ChatGPT in 32.9%; the widest gap among the top 15 was Airwallex, 38.9 points between Gemini and ChatGPT. The figures come from 120 valid answers of 120 planned, to 30 questions asked once of each AI between 29 and 30 October 2026, which named 200 brands in all.

The panels ask different questions about different markets; they are never pooled, and a difference between them is not a finding about either.

Published
Method
v0.9
Benchmark
v1
Version
1
Category
Every edition
DOI
10.5281/zenodo.23792158

Download the report (PDF)DataCite

1Leaderboard

Each panel is ranked on its own questions. The panels ask different questions about different markets; they are never pooled, and a difference between them is not a finding about either.

United States

Top 15 brands by recommendation rate, Corporate cards, United States, collected 29–30 Oct 2026. Percent of decision answers, with 90% interval, overall and per AI.
#BrandRecommendation rate % (90% interval)ChatGPTClaudeGeminiPerplexity
1Ramp86.0 (77.8–94.0)89.781.290.782.3
2Brex77.3 (67.6–87.0)63.582.095.268.3
3Rho26.1 (17.6–35.1)20.445.035.43.7
4BILL Spend & Expense18.7 (10.4–27.4)3.715.939.415.9
5Airwallex18.4 (10.4–27.3)9.322.538.13.7
6BILL Divvy16.0 (8.3–24.8)9.334.414.85.6
7Capital One Spark Cash Plus11.6 (3.7–19.6)0.024.111.111.1
8Navan7.7 (1.8–14.4)7.43.715.93.7
9Ink Business Unlimited6.9 (0.0–16.7)5.611.15.65.6
10Mercury6.3 (2.7–10.3)0.09.315.90.0
11Ink Business Preferred6.0 (0.8–13.8)0.013.05.65.6
12Opal5.2 (0.9–10.4)0.08.512.20.0
13American Express5.1 (0.9–10.3)11.10.09.30.0
14Mercury IO5.1 (1.2–10.0)7.413.00.00.0
15OFX4.6 (1.2–8.1)0.09.39.30.0

Percent of decision answers in which each AI recommended the brand, top 15 of 132 in the United States panel. Overall rate with its 90% interval; the bar draws the interval on a 0–100% scale. Shown to one decimal; the data files carry four.

Europe — composite research panel

Top 15 brands by recommendation rate, Corporate cards, Europe — composite research panel, collected 29–30 Oct 2026. Percent of decision answers, with 90% interval, overall and per AI.
#BrandRecommendation rate % (90% interval)ChatGPTClaudeGeminiPerplexity
1Pleo42.6 (31.7–53.6)32.952.848.136.6
2Revolut Business37.7 (28.7–47.0)35.647.739.428.2
3Spendesk27.4 (18.6–36.9)20.432.436.620.4
4Airwallex23.2 (14.7–31.5)12.516.251.412.5
5Soldo22.1 (13.0–31.8)15.712.536.124.1
6Qonto19.4 (11.1–28.3)16.232.920.48.3
7Moss17.5 (10.3–25.3)12.016.728.712.5
8Payhawk15.2 (8.5–21.8)8.316.731.54.2
9Wallester11.8 (6.8–17.1)3.719.919.93.7
10Wise Business9.1 (4.8–13.5)4.27.912.512.0
11Pliant8.0 (3.1–13.7)0.04.224.13.7
12AirPlus5.1 (0.8–9.7)0.00.012.08.3
13Capital on Tap5.1 (0.0–12.8)7.94.24.24.2
14Wise5.1 (0.8–10.0)7.98.30.04.2
15American Express Business Gold5.0 (0.8–10.8)0.07.94.27.9

Percent of decision answers in which each AI recommended the brand, top 15 of 200 in the Europe — composite research panel panel. Overall rate with its 90% interval; the bar draws the interval on a 0–100% scale. Shown to one decimal; the data files carry four.

2Where the AIs disagree

Among the top 15 of each panel, the brands with the largest gap between the AI that recommended them most and the AI that recommended them least.

United States

Brands among the top 15 with the largest gap between AIs.
BrandHighestLowestGap (points)
RhoClaude 45.0%Perplexity 3.7%41.3
BILL Spend & ExpenseGemini 39.4%ChatGPT 3.7%35.7
AirwallexGemini 38.1%Perplexity 3.7%34.4
BrexGemini 95.2%ChatGPT 63.5%31.8
BILL DivvyClaude 34.4%Perplexity 5.6%28.8

Europe — composite research panel

Brands among the top 15 with the largest gap between AIs.
BrandHighestLowestGap (points)
AirwallexGemini 51.4%ChatGPT 12.5%38.9
PayhawkGemini 31.5%Perplexity 4.2%27.3
QontoClaude 32.9%Perplexity 8.3%24.5
PliantGemini 24.1%ChatGPT 0.0%24.1
SoldoGemini 36.1%Claude 12.5%23.6

3How each AI answers

United States

How each AI answers: medians per answer, and how many answers searched the web.
Per answer, medianChatGPTClaudeGeminiPerplexity
Searched the web30 of 3030 of 3023 of 3030 of 30
Searches per answer4.523.53
Pages found39171215
Pages cited37124
Brands named366.52
Brands recommended35.552
Words per answer232.5410508.5186

Gemini answered 7 of 30 questions without running any web search. That is the model Citewake asked, gemini-3.1-flash-lite, through its API with search available. Across all four AIs, 392 searches were run; 20.4% of them included a year. Every page Gemini reported was one it cited, so its pages found and cited match.

Europe — composite research panel

How each AI answers: medians per answer, and how many answers searched the web.
Per answer, medianChatGPTClaudeGeminiPerplexity
Searched the web30 of 3030 of 3015 of 3030 of 30
Searches per answer6223
Pages found44.5183.515
Pages cited363.54
Brands named466.53
Brands recommended34.553
Words per answer195.5428.5487168.5

Gemini answered 15 of 30 questions without running any web search. That is the model Citewake asked, gemini-3.1-flash-lite, through its API with search available. Across all four AIs, 396 searches were run; 14.9% of them included a year. Every page Gemini reported was one it cited, so its pages found and cited match.

4The sites the AIs cite

United States

The ten domains cited in the most answers.
#DomainAnswers citing itShare
1ramp.com5949.2%
2brex.com5646.7%
3americanexpress.com2117.5%
4support.ramp.com2016.7%
5airwallex.com1915.8%
6bill.com1815.0%
7rho.co1815.0%
8aspireapp.com1613.3%
9nerdwallet.com1613.3%
10navan.com1512.5%

ChatGPT

  1. brex.com43.3%
  2. ramp.com40.0%
  3. americanexpress.com33.3%
  4. support.ramp.com30.0%
  5. bill.com13.3%

Claude

  1. ramp.com60.0%
  2. brex.com30.0%
  3. nerdwallet.com30.0%
  4. rho.co26.7%
  5. aspireapp.com23.3%

Gemini

  1. brex.com70.0%
  2. ramp.com50.0%
  3. airwallex.com43.3%
  4. slash.com40.0%
  5. navan.com36.7%

Perplexity

  1. ramp.com46.7%
  2. brex.com43.3%
  3. support.ramp.com36.7%
  4. americanexpress.com26.7%
  5. bill.com16.7%

Share of the 120 answers whose cited pages include the domain: top ten overall, then the top five within each AI's own 30 answers.

Europe — composite research panel

The ten domains cited in the most answers.
#DomainAnswers citing itShare
1wise.com2218.3%
2spendesk.com1915.8%
3airwallex.com1613.3%
4revolut.com1613.3%
5pleo.io1512.5%
6qonto.com1210.0%
7soldo.com119.2%
8getmoss.com97.5%
9help.revolut.com86.7%
10americanexpress.com75.8%

ChatGPT

  1. pleo.io23.3%
  2. revolut.com23.3%
  3. help.revolut.com16.7%
  4. wise.com13.3%
  5. airwallex.com10.0%

Claude

  1. spendesk.com16.7%
  2. europeanbusinessmagazine.com13.3%
  3. emburse.com10.0%
  4. ramp.com10.0%
  5. rho.co10.0%

Gemini

  1. airwallex.com33.3%
  2. wise.com33.3%
  3. spendesk.com23.3%
  4. soldo.com20.0%
  5. getmoss.com16.7%

Perplexity

  1. revolut.com26.7%
  2. wise.com23.3%
  3. pleo.io20.0%
  4. spendesk.com20.0%
  5. soldo.com10.0%

Share of the 120 answers whose cited pages include the domain: top ten overall, then the top five within each AI's own 30 answers.

5Agreement

United States

On 22 of the 30 questions all four AIs recommended a brand first; they named the same brand first on 6.

Europe — composite research panel

On 26 of the 30 questions all four AIs recommended a brand first; they named the same brand first on 2.

6Method in brief

  • Questions. 60 scored questions in three tiers (head, mid, tail), written as a buyer would ask them and never naming a brand, in two panels of 30 (United States) and 30 (Europe — composite research panel). See the list. A further 15 validation questions are kept private.
  • Asking. Each question was asked once of each AI through its official API, with its own web search on and no location sent. Models: ChatGPT: gpt-6-luna; Claude: claude-haiku-5-5; Gemini: gemini-3.1-flash-lite; Perplexity: perplexity/sonar.
  • Collection. 29 October 2026, 13:45 – 30 October 2026, 04:17 UTC. 240 valid answers of 240 planned: 215 named at least one brand, 25 named none.
  • Reading. One grand master model (Claude Opus 5.5) read the four answers to each question side by side and marked each brand as recommended, mentioned or negative. A brand counts only if its name appears word for word in the answer.
  • Measure. Recommendation rate is the share of decision answers in which the AI recommended the brand. The overall rate weights each AI and each tier equally, so it can differ slightly from a raw count. Intervals are 90%, from a cluster bootstrap that resamples whole questions. Each panel is measured on its own questions: United States, 88 decision answers (22 decision questions, 22 answers from each AI); Europe — composite research panel, 100 decision answers (25 decision questions, 25 answers from each AI). 2 popularity questions (which brand is most used, not which to choose) are reported apart and never counted in the recommendation rate.
  • Method. v0.9, benchmark v1, scoring run 20261030T054023803Z. The full method: citewake.com/methodology.

7Limitations

  • One run. Each question was asked once of each AI, in one window of 14 hours 32 minutes. AI answers vary from run to run; the intervals cover variation across questions, not repeat runs.
  • Two panels, never pooled. The United States panel's questions name the United States. The Europe — composite research panel panel's questions name Austria, Belgium, Germany, Denmark, Spain, France, the United Kingdom, Ireland, Italy, the Netherlands, Poland and Sweden, or Europe as a whole. Questions were in English and no location was sent, so each panel describes the market its questions name, not where an AI was asked from. The panels ask different questions about different markets; they are never pooled, and a difference between them is not a finding about either.
  • Spellings merged. vividmoney was counted as Vivid.
  • Benchmark figures, not market share. These are benchmark visibility figures across a fixed bank of questions with equal weight per tier, not estimates of market share.
  • Top picks are rare. Most answers do not name a single best choice. Even Ramp (United States) was the top pick in only 15.4% and Pleo (Europe — composite research panel) was the top pick in only 5.1% of decision answers, so this report ranks by recommendation rate.

8Disclosure

Citewake is operated by the team that also builds aipozi, Biotree and livedot. Biotree and livedot appear in these categories. They were measured by the same method as every other brand, with no adjustment. None of them was named in this category.

9The questions

Each question links to its page, with the four answers in full, the brands read from them and the pages they cited.

All 60 scored questions, with tier and type
IDQuestionPanelTierType
h01What's the best corporate card for a US company?USheaddecision
h02Which corporate card is best for a US startup?USheaddecision
h03Which US company card lets me set spending limits for each employee?USheaddecision
h04Which US corporate card gives the best rewards or cashback?USheaddecision
h05Which corporate cards are most widely used by US startups?USheaddecision (popularity)
h06How do the main US corporate cards compare?USheaddecision
h07How do I choose a corporate card for a US company?USheadinformational
h08Do US corporate cards require a personal guarantee from the founder?USheadinformational
h09What's the best company card for a small business in the US?USheaddecision
h10What's the difference between a corporate card, a business credit card and a prepaid company card in the US?USheadinformational
h11What's the best corporate card for a company in the UK?Europeheaddecision
h12Which corporate card should a startup in Germany give its employees?Europeheaddecision
h13Which company card in France lets me control what each employee spends?Europeheaddecision
h14What are the main corporate card providers in the Netherlands and how do they compare?Europeheaddecision
h15Which company cards in the Netherlands have no monthly fee?Europeheaddecision
h16Should a company in Spain give staff company cards or keep reimbursing their expenses?Europeheadinformational
h17What's the best company card for a small business in Ireland?Europeheaddecision
h18Which business card in Italy has the lowest fees?Europeheaddecision
h19Which corporate card works best for a company with staff in several European countries?Europeheaddecision
h20Which corporate cards are most widely used by startups in the UK?Europeheaddecision (popularity)
m01Corporate card for a US SaaS company with heavy software and advertising spendUSmiddecision
m02US corporate card that doesn't need a personal guarantee or a high personal credit scoreUSmiddecision
m03US corporate card with a monthly limit above $250,000 for a company's advertising spendUSmiddecision
m04Charge card paid in full each month or a revolving credit card: which suits a US startup?USmidinformational
m05Corporate card for a US company with employees in several countriesUSmiddecision
m06Alternatives to traditional bank corporate cards for a fast-growing US companyUSmiddecision
m07US company card provider that issues a virtual card for each software subscriptionUSmiddecision
m08Company card in the US for staff fuel and travel spendingUSmiddecision
m09US corporate cards with no fees on payments in euros and poundsUSmiddecision
m10US corporate card that syncs spending to accounting software automaticallyUSmiddecision
m11UK company card provider that issues a virtual card for each software subscriptionEuropemiddecision
m12Corporate card for a company in Germany whose staff travel outside Europe oftenEuropemiddecision
m13Corporate card for an agency in the Netherlands buying ads on behalf of clientsEuropemiddecision
m14Corporate cards in France with no fees on payments in US dollarsEuropemiddecision
m15Company card in Ireland for a new company with no trading historyEuropemiddecision
m16Does a company in the UK need corporate cards if it already uses expense management software?Europemidinformational
m17Company card in Spain that sends receipts and spending straight to accounting softwareEuropemiddecision
m18Prepaid company cards in Poland that limit staff to the amount loadedEuropemiddecision
m19Company cards for a ten-person business in ItalyEuropemiddecision
m20Corporate card for a SaaS company in Sweden with heavy software and advertising spendEuropemiddecision
t01US corporate card with budgets per team that reset each monthUStaildecision
t02US corporate card platform that issues and cancels staff cards automatically when people join or leave in our HR systemUStaildecision
t03US corporate card whose limit rises automatically with advertising spendUStaildecision
t04How do I cancel a departing employee's corporate cards and move their subscriptions in a US company?UStailinformational
t05US corporate card programme for several companies with separate limitsUStaildecision
t06How do I tell whether a US corporate card's rewards outweigh its fees?UStailinformational
t07US corporate card platform with single sign-on and role-based admin accessUStaildecision
t08US company card where each card has its own limit and can be frozen instantly from an appUStaildecision
t09US company card to replace petty cash for staff working on siteUStaildecision
t10Who is liable when an employee misuses a company card in the US?UStailinformational
t11UK corporate card that blocks spending at chosen kinds of merchantEuropetaildecision
t12Company card in Germany that prompts staff to upload a receipt straight after each paymentEuropetaildecision
t13Corporate card in France where a manager approves a purchase before the card will workEuropetaildecision
t14What should a company in the Netherlands do when an employee's company card is used fraudulently?Europetailinformational
t15Company card in Ireland that captures VAT details from receipts automaticallyEuropetaildecision
t16Card provider in Spain that issues single-use virtual cards for one-off supplier paymentsEuropetaildecision
t17Business card platform in Austria with a separate card for every employee under one accountEuropetaildecision
t18Company card in Italy where purchases above a set amount need approvalEuropetaildecision
t19Company card provider in Denmark that issues a card for each business trip with its own budget and end dateEuropetaildecision
t20Is a bank-issued business card or a fintech company card better for a startup in Belgium?Europetailinformational

The 15 validation questions are never published.

10Data

  • Every answer: all 240 in full, with the searches each AI ran, the sites it found and cited, and the brands readCSVJSON
  • Every brand in each panel (United States: 132; Europe — composite research panel: 200), every measure, ranked within its panelCSVJSON
  • The reportPDF

Licence: CC BY 4.0. Use and share with credit to Citewake.

11How to cite

APA
Citewake. (2026). Corporate cards: what AI recommends, Citewake Edition 2 (collected 29–30 Oct 2026) (Edition 2) [Data set]. https://doi.org/10.5281/zenodo.23792158
BibTeX
@techreport{citewake-ed2-corporate-cards,
  author      = {{Citewake}},
  title       = {{Corporate cards: what AI recommends, Citewake Edition 2 (collected 29–30 Oct 2026)}},
  institution = {Citewake},
  type        = {Edition 2, data set},
  year        = {2026},
  month       = oct,
  version     = {1},
  doi         = {10.5281/zenodo.23792158},
  url         = {https://citewake.com/editions/2/corporate-cards},
  note        = {Licensed CC BY 4.0}
}

Version 1, published 30 October 2026. Published editions never change; corrections appear as new, dated versions.