- Visibility24
- Citations1
- Sentiment85
- Site quality93
- AI readiness21
AI assistants name Accenture in 18.3% of answers, which is more often than the typical company in its sector at 10%. Its overall score is 42 out of 100, ranking 248th of 2,047 companies. The company's website passes 3 of 14 technical checks for how ready it is for AI tools.
We asked 15 unbranded questions about the technology market: none named Accenture. AI assistants named it in 11 of 60 answers (18.3%). The typical technology company is named in 10.0% of answers. By how often it is named, Accenture ranks 90 of 273 in its sector.
Every dot is a company in the study. Hover one to see it; click to open its report.
This companySame sectorEvery other companyNever named
Five parts, each scored out of 100.
How often AI assistants name the company
How often AI uses the company's own website as a source
How positively AI describes the company
How well built the website's own pages are
How easily AI tools can read and use the website
Visibility is calculated from the answers on this page. How the score is built.
273 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“What are examples of successful technology adoption projects led by management consultants for large enterprises?”
Management consulting firms frequently lead successful technology adoption projects for large enterprises, helping them navigate complex transformations and implement cutting-edge solutions. These projects often involve strategic planning, implementation, and change management to ensure the technology delivers measurable business value.
Here are some examples and common themes in successful technology adoption projects led by management consultants for large enterprises:
1. Artificial Intelligence (AI) and Generative AI Adoption:
IBM's AI Transformation: IBM has focused on helpi …
The AI’s answer as we received it, shortened and not checked for accuracy.
How the mentions in these answers were split between this company and its rivals
Answers naming it, out of answers received
What this website publishes for an AI agent to read, use and buy from, on a scale of six levels.
- 0
- 1
- 2
- 3
- 4
- 5
Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.
- Content Signals
Show every check, for your technical teamHide the checks
- study: 92.0%robots.txtPassed
A valid robots.txt with crawl rules at the site root.
- study: 86.8%SitemapPassed
An XML sitemap listing the pages, ideally referenced from robots.txt.
- study: 0.3%Link headersNot met
Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.
- study: 5.5%DNS for AI DiscoveryNot present
Advertise agent endpoints with SVCB records under _agents.
- study: 1.9%Markdown negotiationNot met
Return a markdown version when asked with Accept: text/markdown, for example at the CDN.
- study: 25.1%llms.txtNot met
Publish an llms.txt with a short summary and the key links.
- study: 93.4%AI bot rulesPartly met
Add explicit robots.txt groups for the main AI crawlers.
- study: 1.4%Content SignalsNot met
Add a Content-Signal line for search, ai-input and ai-train to robots.txt.
- study: 0.2%Web Bot AuthNot present
Only relevant if you run your own agents or crawlers: publish a signing key directory.
- study: 0.3%API CatalogNot met
List public APIs in a linkset at /.well-known/api-catalog.
- study: 11.8%OAuth discoveryNot met
Publish OpenID Connect or OAuth server metadata under /.well-known.
- study: 10.3%OAuth Protected ResourceNot met
Serve protected resource metadata at /.well-known/oauth-protected-resource.
- study: 0.0%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: 0.1%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: 33.7%WebMCPNot met
Register key actions such as search or cart as WebMCP tools.
- study: 0.1%ARD manifestNot met
Publish an ai-catalog.json listing every agent interface.
Score 24 of 100 · 100% of checks could run · checked on October 3, 2026 · www.accenture.com · 2,047 companies scanned
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 checksHide them
- Passedrobots.txt publishedstudy: 85.0%
- PassedXML sitemapstudy: 73.2%
- Not metHTTP Link headers (RFC 8288)study: 29.0%
- Not metMarkdown content negotiationstudy: 8.3%
- Not metllms.txt publishedstudy: 21.7%
- PassedToken budget (page weight)study: 95.2%
- Not metExplicit AI bot rulesstudy: 13.0%
- Not metAPI Catalog (.well-known/api-catalog)study: 0.2%
- Not metOAuth Authorization Server discoverystudy: 10.1%
- Not metOAuth Protected Resource discoverystudy: 9.3%
- Not metMCP Server Cardstudy: 0.0%
- Not metA2A Agent Cardstudy: 0.0%
- Not metWebMCP toolsstudy: 4.2%
- Not metAgent Skills declaredstudy: 0.0%
This website sets no rules for any AI crawler by name, like 84% of the websites whose rules we could read. Every AI crawler follows its general rules.
- GPTBotpartly
- ClaudeBotpartly
- Anthropic-AIpartly
- Google-Extendedpartly
- Applebot-Extendedpartly
- Meta-ExternalAgentpartly
- FacebookBotpartly
- Bytespiderpartly
- CCBotpartly
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBotpartly
- Claude-SearchBotpartly
- PerplexityBotpartly
- Applebotpartly
- Amazonbotpartly
- YouBotpartly
- 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.
How many times each website was listed as a source in these answers
In the study as S&P 500.
- What are examples of successful technology adoption projects led by management consultants for large enterprises?
- What are the best management consulting firms for digital transformation in the United States?
- How can organizations avoid failure in digital transformation initiatives led by external consultants?
- What are the latest trends in management consulting for driving business resilience and continuous reinvention?
- Are end-to-end transformation consulting services worth the investment for multinational companies?
- How are digital transformation consulting fees typically structured for Fortune 500 companies?
- What factors influence the cost of enterprise management consulting projects in the US?
- Business strategy consulting vs. digital transformation advisory—what's the difference?
- Which consulting services specialize in helping large enterprises drive innovation and growth?
- How do technology implementation consulting services compare to traditional management consulting?
- How do consulting firms help public sector organizations achieve operational transformation?
- Can in-house innovation labs replace external digital transformation advisors for public sector agencies?
- What should large organizations look for when choosing a partner for business reinvention?
- Common challenges when working with management consultants on enterprise-wide change projects
- What are effective alternatives to hiring a traditional consulting firm for organizational change?
Columns, left to right: OpenAI, Claude, Perplexity, Gemini. The AI assistants often disagree. Across the study, on 40% of the questions where a company is named, only one of the four names it.
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<a href="https://aeo-audit.rezolve.com/us/accenture.com"><img src="https://aeo-audit.rezolve.com/us/badges/accenture.com.svg" alt="Overall score 42 of 100, US AI Visibility Study 2026" width="280" height="64"></a>