Of 60 answers

The most named companies in the study, and S&P 500 financials, with how many of their 60 AI answers named them.

Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder
Statement period
September 23 and 24, 2026
when the AI assistants were asked
Account no.
193 of 2,219
its rank by overall score
Closing balance

Named in

7of 60 answers

by 4 of 4 assistants

Statement note

What this means for Mercer

AI assistants name this retirement or benefits provider in 11.7% of answers, which is much more often than the typical company in its sector at 0.8%. Its overall score is 41 out of 100, ranking 193rd of 2,219 in the study. The website passes 3 of 14 technical checks for how ready it is for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Mercer by name. AI assistants named it in 7 of the 60 answers. Counting only how often it is named, it ranks 27th of 238 in its sector. The typical investing and wealth company is named in 0.8% of answers.

Overall score
41Overall score
  • Visibility17
  • Citations4
  • Sentiment86
  • Site quality87
  • AI readiness36
Summary of account
Named by AI in
11.7%
7 of 60 answers
Share of mentions
31.8%
of the mentions of it and its 5 peers
AI readiness
3/14
technical checks passed. Typical for its sector: 4
Rank in its sector
13 of 238
by overall score, where the typical investing and wealth company scores 28

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Line itemsSection 01

Every question, and where the company came up

Mercer came up on 4 of 15 questions. Open any window to read that answer.

  1. 01Examples of implementing AI in talent management for enterprise HR teams0/4
  2. 02Is it cost-effective for enterprises to outsource employee benefits consulting?1/4
  3. 03How to address rising costs in workforce healthcare benefits?0/4
  4. 04Common challenges when implementing new health and benefits plans for large employers0/4
  5. 05Are comprehensive investment advisory services worth it for corporate retirement plans?0/4
  6. 06How do fees for institutional investment consulting compare to flat-rate advisory models?0/4
  7. 07What is the typical pricing structure for employee benefits consulting services in the US?0/4
  8. 08Workforce rewards solutions versus traditional benefits packages: which is more effective for engagement?1/4
  9. 09Best approaches for achieving sustainable healthcare cost growth in US corporations0/4
  10. 10What are other ways for enterprises to manage workforce rewards besides third-party consultants?0/4
  11. 11Best strategies for optimizing workforce rewards in large organizations0/4
  12. 12What are the top employee benefits consulting firms trusted by large US enterprises?4/4
  13. 13How can human resources leaders use private markets to diversify retirement plan investments?0/4
  14. 14Alternatives to traditional defined contribution plan consulting for large organizations1/4
  15. 15How does investment consulting differ from retirement plan consulting for institutions?0/4
Total namedOpenAI: 1/15Claude: 1/15Perplexity: 4/15Gemini: 1/15All assistants: 7/60
named the companyanswered without naming itdid not answer

Columns, left to right: OpenAI, Claude, Perplexity, Gemini. Across the study, on 50% of the questions where a company is named, only one AI assistant names it.

Transaction detailSection 02

What Perplexity actually said

An answer that names the company

Perplexitynamed the company

“What are the top employee benefits consulting firms trusted by large US enterprises?”

For large U.S. enterprises, the most trusted employee benefits consulting firms are typically the major national and global players with deep employer-benefits practices: Mercer, Aon, Marsh McLennan Agency / Marsh Health & Benefits, Gallagher, and Alliant.

A practical shortlist, based on the sources provided, would be:

Mercer — explicitly offers employee benefits strategy and consulting and is listed among key employee benefits consulting companies.

Aon — appears in the employee benefits consulting company list and is one of the mos …

The AI’s answer as we received it, shortened and not checked for accuracy.

PayeesSection 03

Where the mentions went

The companies these answers named, and how the mentions were split between this company and its peers.

Also named

CompanyTimes named
  1. 01
    Aon
    6
  2. 02
    Segal
    3
  3. 03
    Gallagher
    3
  4. 04
    Buck
    1

Share of mentions

CompanyShare
  1. Mercer
    31.8%
  2. Aon
    22.7%
  3. Willis Towers Watson
    18.2%
  4. Gallagher
    13.6%
  5. Segal
    9.1%
  6. Buck
    4.5%
ReferrersSection 04

Websites the AI used as sources

How many times each website was listed as a source in these answers

  1. 01
    mercer.com (its own website)
    22
  2. 02
    aon.com
    14
  3. 03
    shrm.org
    12
  4. 04
    achievers.com
    10
  5. 05
    clutch.co
    9
  6. 06
    blackrock.com
    8
  7. 07
    ubs.com
    7
  8. 08
    dol.gov
    7
  9. 09
    justdial.com
    7
  10. 10
    bakertilly.com
    6

Mercer is in the study as a retirement or benefits provider.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Perplexity
4/15
Gemini
1/15
Claude
1/15
OpenAI
1/15
Market comparisonSection 06

How Mercer compares with all 2,219 companies

Every tower is a company in the study, taller for a higher overall score and lit where AI assistants named it. Its own group stays lit. Hover a tower to see it, and click to open it.

What makes up the score

Each part is scored out of 100.

Visibility
17

How often AI assistants name the company, and how that compares with its peers

Citations
4

How often AI uses the company's own website as a source

Sentiment
86

How positively AI describes the company

Site quality
87

How well built the website's own pages are

AI readiness
36

How easily AI tools can read and use the website

Visibility is calculated from the answers on this page. How the score is built.

Against its sectorSection 07

Compared with investing and wealth companies

238 companies in this sector. The gold tick on each bar is the typical company.

Overall score
41
Ranks 13 of 238. Typical company: 28
Named in answers
11.7%
Ranks 27 of 238. Typical company: 0.8%
AI readiness
36
Ranks 15 of 238. Typical company: 29
Against its categorySection 08

Compared with retirement and benefits providers

10 companies in this category. The gold tick on each bar is the typical company.

Overall score
41
Ranks 2 of 10. Typical company: 31
Named in answers
11.7%
Ranks 2 of 10. Typical company: 1.7%
AI readiness
36
Ranks 2 of 10. Typical company: 21
AI agentsSection 09

Ready for AI agents

What this website publishes for an AI agent to read, use and pay through, on a scale of six levels.

  1. 0
  2. 1
  3. 2
  4. 3
  5. 4
  6. 5

Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.

To reach level 2:
  • Content Signals
Can an AI agent check out here?

Not by itself. Mercer publishes none of the agent payment protocols we look for. An agent would have to click through the website like a person.

Agent payment protocols
  • x402Not present
  • MPPNot present
  • AP2Not present
  • ACPNot present
  • UCPNot present
Interfaces for AI agents
  • MCP Server CardNot present
  • A2A Agent CardNot present
  • Agent SkillsNot present
  • API CatalogNot present
  • llms.txtNot present
  • WebMCPCould not check
Show every check, for your technical team
Discoverability
77 of 100
  • robots.txtPassed

    A valid robots.txt with crawl rules at the site root.

    study: 86.1%
  • SitemapPassed

    An XML sitemap listing the pages, ideally referenced from robots.txt.

    study: 87.9%
  • Link headersNot met

    Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.

    study: 1.5%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 4.3%
Content accessibility
0 of 100
  • Markdown negotiationNot met

    Return a markdown version when asked with Accept: text/markdown, for example at the CDN.

    study: 6.2%
  • llms.txtNot met

    Publish an llms.txt with a short summary and the key links.

    study: 31.0%
Bot access control
32 of 100
  • AI bot rulesPartly met

    Add explicit robots.txt groups for the main AI crawlers.

    study: 92.7%
  • Content SignalsNot met

    Add a Content-Signal line for search, ai-input and ai-train to robots.txt.

    study: 2.3%
  • Web Bot AuthNot present

    Only relevant if you run your own agents or crawlers: publish a signing key directory.

    study: 0.3%
APIs, auth and MCP
0 of 100
  • API CatalogNot met

    List public APIs in a linkset at /.well-known/api-catalog.

    study: 1.3%
  • OAuth discoveryNot met

    Publish OpenID Connect or OAuth server metadata under /.well-known.

    study: 6.3%
  • OAuth Protected ResourceNot met

    Serve protected resource metadata at /.well-known/oauth-protected-resource.

    study: 5.3%
  • auth.mdNot met

    Publish an auth.md describing how agents sign in.

    study: 0.2%
  • MCP Server CardNot met

    Offer an MCP server and publish its server card under /.well-known.

    study: 0.8%
  • A2A Agent CardNot met

    Publish an agent card at /.well-known/agent-card.json.

    study: 0.2%
  • Agent SkillsNot met

    Publish a skills index with the main tasks agents can do.

    study: 1.0%
  • WebMCPCould not check

    Register key actions such as search or cart as WebMCP tools.

    study: 0.0%
  • ARD manifestNot met

    Publish an ai-catalog.json listing every agent interface.

    study: 0.2%

Score 25 of 100 · 97% of checks could run · checked on October 5, 2026 · www.mercer.com · 2,200 companies scanned

See how every company did, and how this was measured.

AI readinessSection 10

The checks behind the AI readiness score

3 of 14 passed. This list is for your technical team. The percentage is how many companies in the study pass each check.

These 14 checks ran during the audit and are what the AI readiness part of the overall score counts. The scan above ran later and is stricter on Link headers and Markdown, so a check can pass here and not there.

Show the 14 checks

Discoverability

  • Passedrobots.txt publishedstudy: 85.1%
  • PassedXML sitemapstudy: 79.4%
  • Not metHTTP Link headers (RFC 8288)study: 42.5%

Content Accessibility

  • Not metMarkdown content negotiationstudy: 7.4%
  • Not metllms.txt publishedstudy: 28.1%
  • PassedToken budget (page weight)study: 97.3%

Bot Access Control

  • Not metExplicit AI bot rulesstudy: 11.5%

API / Auth / MCP

  • Not metAPI Catalog (.well-known/api-catalog)study: 1.1%
  • Not metOAuth Authorization Server discoverystudy: 5.2%
  • Not metOAuth Protected Resource discoverystudy: 4.6%
  • Not metMCP Server Cardstudy: 0.2%
  • Not metA2A Agent Cardstudy: 0.0%
  • Not metWebMCP toolsstudy: 0.3%
  • Not metAgent Skills declaredstudy: 0.1%
AI crawlersSection 11

What AI crawlers may read (robots.txt)

This website sets no rules for any AI crawler by name, like 86% of the websites whose rules we could read. Every AI crawler follows its general rules.

Training AI

  • GPTBotpartly
  • ClaudeBotpartly
  • Anthropic-AIpartly
  • Google-Extendedpartly
  • Applebot-Extendedpartly
  • Meta-ExternalAgentpartly
  • FacebookBotpartly
  • Bytespiderpartly
  • CCBotpartly
  • Diffbotpartly
  • Omgilibotpartly

AI search

  • OAI-SearchBotpartly
  • Claude-SearchBotpartly
  • PerplexityBotpartly
  • Applebotpartly
  • Amazonbotpartly
  • YouBotpartly

Answering questions

  • ChatGPT-Userpartly
  • Claude-Userpartly
  • Perplexity-Userpartly
  • DuckAssistBotpartly
  • MistralAI-Userpartly

Read from the website’s own rules file (robots.txt). An asterisk marks a crawler the file names. The rest follow its general rules. “Partly” means only some pages are blocked.

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ShareSection 12

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Overall score 41 of 100 badge for Mercer

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