Overview Leaderboard Methodology
Industry Report

Travel and Expense (T&E) Management Systems

Integrated systems that manage business travel booking, expense submission, policy compliance, and reimbursement workflows for organizations.

Brands tracked: 36
Brands analyzed: 36
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 281
Total responses: 1,435
Top Brand Overall?
SAP Concur
90/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Brex
83

Highest score on the LBA metric in this industry.

Authority Leader?
SAP Concur
96

Highest score on the Authority metric in this industry.

TOM Leader?
SAP Concur
100

Highest score on the TOM metric in this industry.

SAP Concur is the default answer in AI responses for Travel and Expense (T&E) Management Systems

SAP Concur and Navan together dominate AI responses for Travel and Expense (T&E) Management Systems. Both brands consistently surface unprompted, with the model treating them as the default answers for most category queries. Brands outside the top two face a structural disadvantage: users are usually given these two before the model even considers alternatives.

Brand Leaderboard All 36 Travel and Expense (T&E) Management Systems brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
SAP Concur
concur.com
 76
96
100
90
2
Navan
navan.com
 74
81
93
82
3
Ramp
ramp.com
 82
69
83
77
4
Expensify
expensify.com
 77
57
77
70
5
Brex
brex.com
 83
45
69
64
6
Zoho
zoho.com
 79
34
54
53
7
Emburse
emburse.com
 71
19
43
39
8
Coupa
coupa.com
 70
13
42
35
9
TravelPerk
travelperk.com
 76
8
24
26
10
Egencia
egencia.com
 72
7
14
21
11
Rydoo
rydoo.com
 58
6
14
18
12
Spendesk
spendesk.com
 73
7
7
18
13
Certify
certify.com
 63
6
9
17
14
Chrome River
chromeriver.com
 67
7
7
17
15
Pleo
pleo.io
 70
7
7
17
16
Airbase
airbase.com
 62
6
7
16
17
NetSuite CRM
netsuite.com
 55
6
9
16
18
Payhawk
payhawk.com
 67
7
7
16
19
Deem
deem.com
 48
5
9
15
20
Fyle
fylehq.com
 61
6
6
15
21
Happay
happay.com
 62
6
6
15
22
Soldo
soldo.com
 60
6
6
15
23
TravelBank
travelbank.com
 61
6
6
15
24
webexpenses
webexpenses.com
 59
6
6
15
25
Expensya
expensya.com
 56
6
6
14
26
QuickBooks Live
intuit.com
 55
6
6
14
27
Xero
xero.com
 56
6
6
14
28
Abacus
abacus.com
 52
5
5
13
29
Circula
circula.com
 51
5
5
13
30
DATABASICS
databasics.com
 53
5
5
13
31
Moss
getmoss.com
 51
5
5
13
32
Yokoy
yokoy.ai
 47
5
5
12
33
BILL
bill.com
 43
4
4
11
34
Center
centerexpense.com
 37
4
4
10
35
Routespring
routespring.com
 26
3
3
7
36
Mesh
mesh.ai
 22
2
2
6

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 281 shared Travel and Expense (T&E) Management Systems prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 281 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →