- Visibility16
- Citations2
- Sentiment58
- Site quality80
- AI readiness36
AI assistants name Amdocs in 10% of answers, matching the typical company in the technology sector. Its overall score is 34 out of 100, ranking 904th of 2,047 companies. The company's website passes 4 out of 14 technical checks for AI tool readiness.
We asked 15 unbranded questions about the technology market: none named Amdocs. AI assistants named it in 6 of 60 answers (10.0%). The typical technology company is named in 10.0% of answers. By how often it is named, Amdocs ranks 132 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 the best software solutions for telecom companies looking to accelerate digital transformation?”
Telecom companies are increasingly focusing on digital transformation to remain competitive, improve operational efficiency, and enhance customer experiences in a rapidly evolving market. This involves adopting new technologies and business models to modernize infrastructure and diversify offerings.
Key software solutions and areas for digital transformation in the telecom industry include:
1. Business Support Systems (BSS) Modernization
Billing, Charging, and Revenue Management: Modern BSS solutions are essential for quickly launching new plans, supporting complex bundles, and m …
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 0: Not yet agent-ready. Agents struggle to find basic information about the site.
- 2 of robots.txt, Sitemap, Link headers
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%SitemapNot met
Serve an XML sitemap and reference it 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.txtPassed
An llms.txt that tells language models what the site offers.
- study: 93.4%AI bot rulesPassed
Explicit robots.txt rules for AI crawlers such as GPTBot, ClaudeBot and PerplexityBot.
- 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%WebMCPCould not check
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 34 of 100 · 97% of checks could run · checked on October 5, 2026 · www.amdocs.com · 2,047 companies scanned
4 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%
- Not metXML sitemapstudy: 73.2%
- Not metHTTP Link headers (RFC 8288)study: 29.0%
- Not metMarkdown content negotiationstudy: 8.3%
- Passedllms.txt publishedstudy: 21.7%
- PassedToken budget (page weight)study: 95.2%
- PassedExplicit 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 rules for 7 AI crawlers by name. All others follow its general rules.
- GPTBot*partly
- ClaudeBot*partly
- Anthropic-AI*partly
- Google-Extendedpartly
- Applebot-Extendedpartly
- Meta-ExternalAgentpartly
- FacebookBotpartly
- Bytespider*partly
- CCBot*allowed
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBotpartly
- Claude-SearchBotpartly
- PerplexityBot*partly
- Applebotpartly
- Amazonbotpartly
- YouBotpartly
- ChatGPT-User*partly
- 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 US-listed.
- What are the best software solutions for telecom companies looking to accelerate digital transformation?
- How do cloud-native telecom software platforms compare to traditional on-premises solutions?
- What pricing models are common for digital BSS/OSS systems in the US?
- What are alternatives to comprehensive telecom business support systems?
- What are use cases for 5G monetization solutions within US media companies?
- Which telecom and media platforms help enterprises innovate their service offerings?
- How can telecommunications enterprises leverage automation for network management?
- Are integrated digital billing platforms effective for media and telecom companies?
- How can telecom companies minimize revenue leakage in digital platforms?
- What features should telecom enterprises look for in customer engagement software?
- How are telecom software platforms typically priced for large-scale enterprises?
- Is investing in AI-powered customer experience software worthwhile for telecom operators?
- What are the key differences between telecom OSS and BSS solutions?
- What are effective ways to reduce service downtime in media management software?
- Which types of modular solutions can replace legacy media management platforms?
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/amdocs.com"><img src="https://aeo-audit.rezolve.com/us/badges/amdocs.com.svg" alt="Overall score 34 of 100, US AI Visibility Study 2026" width="280" height="64"></a>