Overview Leaderboard Methodology
Industry Report

Enterprise Service Management Suites

Comprehensive platforms that extend ticketing into ITSM, asset management, and cross-departmental workflows for large enterprises.

Brands tracked: 33
Brands analyzed: 33
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 263
Total responses: 1,330
Top Brand Overall?
ServiceNow
96/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
ServiceNow
89

Highest score on the LBA metric.

Authority Leader?
ServiceNow
100

Highest score on the Authority metric.

TOM Leader?
ServiceNow
100

Highest score on the TOM metric.

ServiceNow is the default answer in AI responses for Enterprise Service Management Suites

When users ask ChatGPT, Claude, or Gemini about Enterprise Service Management Suites, ServiceNow is the brand that surfaces first - unprompted, consistently, and usually at the top of any list the model generates. Freshservice is a close second, but the gap between them is meaningful. If you're competing in this space and you're not in the top handful, you're effectively invisible to AI-driven discovery.

Brand Leaderboard All 33 Enterprise Service Management Suites brands ranked

Ranked by overall AI Visibility Score (geometric mean of LBA, Authority, and TOM). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
ServiceNow
servicenow.com
 89
100
100
96
2
Freshservice
freshservice.com
 77
60
72
69
3
ManageEngine ServiceDesk Plus
manageengine.com
 72
17
63
43
4
Atlassian
atlassian.com
 85
14
37
35
5
TOPdesk
topdesk.com
 64
5
49
24
6
Zendesk
zendesk.com
 82
3
9
13
7
Freshworks
freshworks.com
 79
0
22
3
8
Cherwell
cherwell.com
 59
0
15
2
9
HaloITSM
haloitsm.com
 61
0
7
2
10
OpenText SMAX
opentext.com
 54
0
12
2
11
SysAid
sysaid.com
 68
0
21
2
12
4me
4me.com
 65
0
2
1
13
EasyVista
easyvista.com
 54
0
2
1
14
Hornbill
hornbill.com
 36
0
6
1
15
TeamDynamix
teamdynamix.com
 61
0
1
1
16
Alemba Service Manager
alemba.com
 38
0
0
0
17
Alloy Navigator
alloysoftware.com
 54
0
0
0
18
A
assyst
assyst.com
 35
0
0
0
19
BMC Remedy
bmc.com
 62
0
0
0
20
BOSS Solutions
boss-solutions.com
 25
0
0
0
21
Cireson
cireson.com
 50
0
0
0
22
EcholoN
echolon.de
 13
0
0
0
23
Efecte
efecte.com
 47
0
0
0
24
InvGate Service Desk
invgate.com
 55
0
0
0
25
Ivanti Service Manager
ivanti.com
 64
0
0
0
26
Matrix42
matrix42.com
 56
0
0
0
27
Motadata ServiceOps
motadata.com
 39
0
0
0
28
Omnitracker
omnitracker.com
 39
0
0
0
29
OTRS
otrs.com
 56
0
0
0
30
Provance
provance.com
 5
0
0
0
31
SolarWinds Web Help Desk
solarwinds.com
 51
0
0
0
32
SummitAI
summitai.com
 32
0
0
0
33
S
Sunrise ITSM
sunrise.co.uk
 5
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 263 shared Enterprise Service Management Suites 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
Geometric mean of LBA, Authority and TOM: (LBA × Authority × TOM)^(1/3). Geometric mean is used so that any single weak metric pulls the overall score down, rather than being masked by strength elsewhere.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 263 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 →