What is an AI Readiness Score?

An AI Readiness Score is a measure from 0 to 100 that indicates how well your website can be read, understood, and recommended by AI agents like ChatGPT, Perplexity, Claude, and Google AI Overviews. It evaluates 48 specific checks across 5 categories: Access & Crawlability, Readability & Structure, Identity & Trust, Integration & Discovery, and Answerability & Content.

How does Score for AI work?

Score for AI fetches your website and analyzes it across 48 checks in 5 categories. We examine your robots.txt for AI bot access, check structured data and Schema.org markup, evaluate content depth and readability, verify meta tags and OpenGraph data, and test for AI-specific protocols like agent.json and MCP endpoints. Results are delivered in about 30 seconds.

Why should I care about AI readiness?

AI agents are rapidly becoming a primary way people find information. Google AI Overviews have reduced organic click-through rates by up to 61%. Gartner predicts traditional search volume will drop 25% by 2026. If AI agents cannot properly read and understand your website, you risk becoming invisible to a growing share of potential customers.

What AI agents does this cover?

Score for AI checks compatibility with all major AI agents including ChatGPT (GPTBot), Claude (ClaudeBot), Google AI Overviews (Google-Extended), Perplexity (PerplexityBot), Amazon (Amazonbot), Apple Intelligence (Applebot-Extended), Meta AI (meta-externalagent), Microsoft Copilot, and Common Crawl (CCBot).

How is the score calculated?

The score is calculated by running 48 individual checks across 5 weighted categories. Each check is pass/fail and contributes to its category score. The final score is a weighted average: Access & Crawlability, Readability & Structure, Identity & Trust, Integration & Discovery, and Answerability & Content. The maximum score is 100.

What's included in the free scan vs paid report?

The free scan gives you your overall AI readiness score plus a category-level breakdown showing where you stand in each of the 5 areas. The paid Full Report ($29) provides detailed check-by-check results, specific fix recommendations with code examples, priority ranking of issues, and competitive benchmarking against your industry.

How can I improve my AI readiness score?

Common improvements include: allowing AI bots in your robots.txt, adding Schema.org structured data, implementing proper meta tags and OpenGraph markup, creating a sitemap.xml, adding an RSS feed, writing substantial and well-structured content with proper heading hierarchy, and implementing AI-specific protocols like .well-known/agent.json.

How often should I scan my website?

We recommend scanning after any major website update, content change, or CMS migration. For active websites, a monthly scan helps ensure your AI readiness stays high as search engines and AI agents evolve their requirements. The AI landscape changes rapidly, so regular monitoring is important.

Key Findings

The overall average AI readiness score across all 4,100,000+ scanned websites is 34 out of 100. This means the typical website fails more than half of the 48 AI readiness checks. The gap between the best and worst industries is significant — digital agencies average 44 while government sites average just 19.

Industry Breakdown

Digital Agencies (Avg: 44)

Agencies lead because they tend to be early adopters of web standards and often build custom sites with proper structured data. However, even at 44/100, there's significant room for improvement. Common gaps: missing agent.json, no llms.txt, and incomplete Schema.org implementation.

SaaS / Tech (Avg: 42)

Tech companies score well on technical fundamentals (semantic HTML, fast response times) but often lag on content depth and AI-specific discovery protocols. Many SaaS sites have marketing pages with minimal text content — great for conversion, poor for AI citation.

Media / Publishing (Avg: 38)

Surprisingly low given their content focus. The main issue: many publishers actively block AI bots in robots.txt to protect their content from being used for AI training. While understandable, this also prevents AI agents from citing them in responses — a trade-off that may cost more traffic than it protects.

E-commerce (Avg: 31)

E-commerce sites typically have good product structured data (for Google Shopping) but poor AI readiness beyond that. Common issues: thin product descriptions, no FAQ content, missing agent.json, and heavy JavaScript rendering that AI crawlers struggle with.

Local Business (Avg: 22)

Local businesses — restaurants, retail stores, service providers — score lowest among commercial sites. Most use template-based website builders with minimal customization, thin content, and no structured data beyond what the platform provides by default.

Government (Avg: 19)

Government websites score lowest overall. Legacy technology stacks, aggressive bot blocking policies, minimal structured data, and content organized for bureaucratic rather than informational purposes all contribute. Ironically, government data is among the most frequently queried in AI systems.

What Top Performers Do Differently

Websites scoring above 70/100 (the top 5%) share these characteristics:

Comprehensive structured data — Not just Organization, but Article, Product, FAQ, and BreadcrumbList schemas
Open AI access — All major AI bots explicitly allowed in robots.txt
Content depth — Average of 1,200+ words per page with specific facts and data
Full discovery stack — Sitemap, RSS, agent.json, and llms.txt all present
Fresh content — Updated within the last 30 days with proper dateModified signals

Where Does Your Industry Stand?

Scan your website to see how you compare against your industry benchmark. The Full Report includes competitive benchmarking that shows exactly where you stand relative to similar sites.

AI Readiness Fundamentals and Implementation Guide

Understanding AI Readiness for Modern Websites

AI readiness encompasses comprehensive website optimization enabling artificial intelligence agents to effectively access, parse, understand, and recommend content across multiple platforms including ChatGPT, Claude, Perplexity, Google AI, and emerging AI search systems.

Technical Infrastructure Requirements for AI Compatibility

Server configuration optimization includes robots.txt AI bot permissions for GPTBot, ClaudeBot, Google-Extended, PerplexityBot, Amazonbot, Applebot-Extended, and CCBot crawlers enabling training data collection and search integration capabilities.

Content Structure and Semantic Markup Optimization

Semantic HTML implementation with proper heading hierarchy, article structuring, section organization, and list formatting facilitates machine comprehension and automated knowledge extraction for AI training and response generation systems.

Structured Data and Schema.org Implementation

JSON-LD structured data markup using Schema.org vocabularies provides machine-readable context including Organization, Person, Product, Service, Article, and specialized AI-specific schemas enabling enhanced understanding and factual extraction.

AI-Specific Protocols and Emerging Standards

Implementation of llms.txt documentation, agent.json metadata files, MCP endpoint configuration, and API documentation enables direct AI agent integration and automated content discovery across artificial intelligence platforms.

Continuous Monitoring and Performance Optimization

Regular analysis ensures sustained AI readiness performance as artificial intelligence technologies evolve, requirement standards change, and emerging protocols develop across major platforms and search engine integrations.

AI Readiness by Industry: Average Scores and Benchmarks