- Visibility11
- Citations1
- Sentiment50
- Site quality80
- AI readiness36
AI assistants name Carrier Global in 5% of answers, which is about as often as the typical company in the industrial sector. Carrier Global has an overall score of 31 out of 100, ranking 1,145th of 2,047 companies. Its website passes 3 out of 14 technical checks measuring readiness for AI tools.
We asked 15 unbranded questions about the industrial market: none named Carrier Global. AI assistants named it in 3 of 60 answers (5.0%). The typical industrial company is named in 5.0% of answers. By how often it is named, Carrier Global ranks 116 of 246 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.
246 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“What are the best intelligent climate control systems for large commercial buildings?”
Intelligent climate control systems for large commercial buildings leverage AI, IoT sensors, and predictive analytics to optimize energy use, reduce operational costs, and enhance occupant comfort. These systems move beyond traditional, fixed-schedule HVAC operation to dynamic, real-time adjustments based on various factors.
Here are some of the best intelligent climate control systems and features for large commercial buildings:
Key Technologies and Features:
AI-Powered Optimization: AI and machine learning algorithms analyze data from smart sensors, occupancy trends, and weathe …
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 met
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 24 of 100 · 97% of checks could run · checked on October 5, 2026 · www.carrier.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.
- Are advanced building automation systems for climate control worth the investment?
- Alternatives to traditional refrigeration units for sustainable cold storage in food processing plants?
- What is the average cost range for installing an industrial HVAC and energy management system in the U.S.?
- Most innovative climate and energy solutions for schools looking to enhance learning environments?
- Which energy management platforms offer both HVAC and refrigeration solutions for industrial needs?
- What climate control solutions are best for improving air quality in healthcare facilities?
- How can retail spaces reduce energy costs using modern building automation?
- What are the best intelligent climate control systems for large commercial buildings?
- What are alternatives to centralized HVAC systems for energy-efficient climate control in warehouses?
- Is it cost-effective for factories to upgrade to intelligent energy management platforms?
- Why might a warehouse's smart energy solution not be meeting sustainability goals?
- Variable refrigerant flow versus chilled water systems for office complexes—how do they stack up?
- Common problems when integrating new HVAC controls into existing commercial systems?
- How do ongoing maintenance costs compare between traditional and intelligent climate solutions?
- How do different types of commercial HVAC systems compare for energy efficiency?
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/carrier.com"><img src="https://aeo-audit.rezolve.com/us/badges/carrier.com.svg" alt="Overall score 31 of 100, US AI Visibility Study 2026" width="280" height="64"></a>