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
October 9 to 14, 2026
when the AI assistants were asked
Account no.
704 of 2,219
its rank by overall score
Place in its category
41st of 177 consultancies
Closing balance

Named in

2of 60 answers

by 2 of 4 assistants

Statement note

What this means for Alvarez & Marsal

AI assistants rarely name this consultancy, appearing in only 2 of 60 answers, with Bain & Company and Protiviti also named. Its overall score is 34 out of 100, which ranks 704th of 2,219 companies and 92nd in its sector. The website passes 3 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Alvarez & Marsal by name. AI assistants named it in 2 of the 60 answers. Counting only how often it is named, it ranks 96th of 346 in its sector. The typical advisory or services firm is named in 0.0% of answers.

Named fewer than three times in total. Read this as a sign that AI assistants rarely bring this company up, not as an exact comparison with its peers.

Overall score
34Overall score
  • Visibility5
  • Citations0
  • Sentiment100
  • Site quality67
  • AI readiness21
Summary of account
Named by AI in
3.3%
2 of 60 answers
Share of mentions
10.5%
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
92 of 346
by overall score, where the typical advisory or services firm scores 27

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Line itemsSection 01

Every question, and where the company came up

Alvarez & Marsal came up on 2 of 15 questions. Open any window to read that answer.

  1. 01How to address gaps in financial infrastructure identified during a consulting engagement0/4
  2. 02Are consulting engagements effective for long-term organizational transformation?0/4
  3. 03Common reasons why consulting-led performance improvement initiatives might fail0/4
  4. 04Best approaches for leveraging consulting firms to scale corporate services teams0/4
  5. 05Ways management consulting supports mergers and acquisitions in large organizations0/4
  6. 06Are management consulting firms negotiable on project-based pricing?0/4
  7. 07What are the differences between financial restructuring consultants and general management consultants?0/4
  8. 08Is hiring a professional services firm worth it for navigating complex financial situations?0/4
  9. 09Typical fee structures for management consulting services in the US0/4
  10. 10In-house versus outsourced professional services for regulatory risk management0/4
  11. 11Top professional services firms for improving operational efficiency in large corporations1/4
  12. 12What are the best management consulting services for organizations facing regulatory challenges in the US?1/4
  13. 13Alternatives to traditional management consulting for solving operational challenges0/4
  14. 14How do strategy consulting and operational consulting differ for corporate clients?0/4
  15. 15How can professional services help health systems strengthen capital planning?0/4
Total namedOpenAI: 0/15Claude: 1/15Perplexity: 0/15Gemini: 1/15All assistants: 2/60
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 Claude actually said

An answer that names the company

Claudenamed the company

“Top professional services firms for improving operational efficiency in large corporations”

… Alvarez & Marsal: Offers professional services focused on corporate performance improvement, turnaround management, and financial restructuring, with advisory services like cost reduction and operational improvement tied to business transformation.

AlixPartners: Specializes in operational turnarounds and performance improvement for companies in distress, with consultants known for working alongside client teams on implementation.

DXC Technology: A US company operating in more than 70 countries that combines technical delivery with management consulting at the process, sys …

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
    Bain & Company
    3
  2. 02
    Protiviti
    2
  3. 03
    AlixPartners
    2
  4. 04
    FTI Consulting
    2

Share of mentions

CompanyShare
  1. Bain & Company
    31.6%
  2. FTI Consulting
    15.8%
  3. AlixPartners
    15.8%
  4. Protiviti
    15.8%
  5. Alvarez & Marsal
    10.5%
  6. Navigant (now part of Guidehouse)
    10.5%
ReferrersSection 04

Websites the AI used as sources

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

  1. 01
    casebasix.com
    8
  2. 02
    deloitte.com
    7
  3. 03
    hackingthecaseinterview.com
    6
  4. 04
    linkedin.com
    5
  5. 05
    consulting.us
    5
  6. 06
    consultingdemand.com
    5
  7. 07
    airiodion.com
    4
  8. 08
    alphaapexgroup.com
    4
  9. 09
    consultingquest.com
    3
  10. 10
    forvismazars.us
    3

Alvarez & Marsal is in the study as a consultancy.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Claude
1/15
Gemini
1/15
OpenAI
0/15
Perplexity
0/15
Market comparisonSection 06

How Alvarez & Marsal 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
5

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

Citations
0

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

Sentiment
100

How positively AI describes the company

Site quality
67

How well built the website's own pages are

AI readiness
21

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 advisory and services firms

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

Overall score
34
Ranks 92 of 346. Typical company: 27
Named in answers
3.3%
Ranks 96 of 346. Typical company: 0.0%
AI readiness
21
Ranks 228 of 346. Typical company: 29
Against its categorySection 08

Compared with consultancies

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

Overall score
34
Ranks 38 of 177. Typical company: 27
Named in answers
3.3%
Ranks 37 of 177. Typical company: 0.0%
AI readiness
21
Ranks 113 of 177. Typical company: 29
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

The website turns away requests that do not come from a browser. AI agents that say what they are meet the same refusal.

Can an AI agent check out here?

Not by itself. Alvarez & Marsal 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
93 of 100
  • robots.txtPassed

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

    study: 86.1%
  • SitemapPartly met

    Serve an XML sitemap and reference it from robots.txt.

    study: 87.9%
  • Link headersCould not check

    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 · 92% of checks could run · checked on October 9, 2026 · www.alvarezandmarsal.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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