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Forbes 2025 AI 50 SEO Scorecard

We analyzed the top 50 companies from Forbes AI 50 list to evaluate their AI SEO readiness and discoverability by LLMs and AI agents. Each website was scored across six key categories that determine how well they can be discovered, understood, and cited by AI systems.

2025
AI SEO
Industry Report

AI SEO Readiness Rankings

Rank
Company
Overall
Report
Page
Structure
Format
Accessibility
LLM Judge
Crawlability
Readability
1
Windsurf
75
Homepage
38
79
93
80
74
100
2
Synthesia
74
Homepage
83
100
77
80
84
29
3
Databricks
72
Homepage
29
100
100
80
74
71
4
Hebbia
72
Homepage
21
100
100
80
59
100
5
Sierra
72
Homepage
88
100
90
50
84
29
6
Fireworks AI
72
Homepage
36
100
100
75
80
64
7
Figure
70
Homepage
25
36
100
70
73
100
8
Writer
69
Homepage
97
100
77
60
71
14
9
Decagon
69
Homepage
30
100
100
85
83
29
10
Speak
69
Homepage
25
71
83
80
72
100
11
Anthropic
68
Product
25
78
93
60
76
100
12
Lambda
67
Homepage
38
100
100
70
79
29
13
Glean
65
Homepage
50
100
83
80
73
14
14
Harvey
65
Homepage
36
100
100
70
85
14
15
Photoroom
64
Homepage
26
100
100
60
76
50
16
Abridge
63
Homepage
29
71
93
80
70
29
17
Cohere
63
Homepage
38
100
93
60
80
29
18
Vast
63
Homepage
32
100
93
70
76
29
19
Thinking Machines
63
Homepage
18
50
100
100
52
29
20
Vannevar Labs
62
Homepage
18
100
100
90
43
29
21
Captions
61
Homepage
30
79
73
55
70
86
22
Clay
60
Homepage
40
100
93
60
73
14
23
Snorkel
60
Homepage
94
100
27
65
70
29
24
Crusoe
58
Homepage
19
79
100
65
61
29
25
SambaNova
58
Homepage
36
100
93
40
79
29
26
Hugging Face
57
Homepage
36
100
93
50
60
29
27
LangChain
56
Homepage
20
100
90
60
66
29
28
Skild AI
55
Homepage
25
50
90
70
50
29
29
Together.ai
54
Homepage
25
100
90
50
70
14
30
ElevenLabs
54
Homepage
36
100
90
45
81
0
31
Scale
54
Homepage
24
79
100
45
76
14
32
Coactive
54
Homepage
26
100
90
50
73
14
33
Mercor
53
Homepage
30
50
17
70
76
100
34
Runway
52
Homepage
15
64
100
60
39
29
35
Notion
52
Homepage
31
100
17
55
88
86
36
StackBlitz
51
Homepage
36
79
90
35
50
29
37
OpenEvidence
49
Homepage
25
36
33
75
61
64
38
Luminance
42
Homepage
36
100
10
80
54
14
39
Mistral
41
Homepage
31
100
27
50
76
14
40
Baseten
40
Homepage
32
79
0
60
81
29
41
Suno
36
Homepage
76
0
23
0
62
36
42
World Labs
34
Homepage
25
0
90
0
57
0
-
Cursor
-
Bot Blocked
Homepage
-
-
-
-
-
-
-
OpenAI
-
Bot Blocked
Homepage
-
-
-
-
-
-
-
XAI
-
Bot Blocked
Homepage
-
-
-
-
-
-
-
DeepL
-
Thin Content
Homepage
-
-
-
-
-
-
-
Midjourney
-
Thin Content
Homepage
-
-
-
-
-
-
-
Perplexity
-
No Landing Page
Homepage
-
-
-
-
-
-
-
Pika
-
No Landing Page
Homepage
-
-
-
-
-
-
-
Sakana
-
Thin Content
Homepage
-
-
-
-
-
-

Key Findings

Overall Performance

Our analysis of the Forbes AI 50 companies reveals significant gaps in AI SEO readiness across the industry. While these companies are at the forefront of AI innovation, many have not yet optimized their web presence for AI discovery and understanding.
Average overall score was 60/100, indicating substantial room for improvement.
Only 14% of companies scored above 70 in overall AI readiness.
Top 5 companies averaged 73/100, showing clear leaders in the space.

Common Deficiencies

The most common deficiencies were found in structured data implementation and AI-friendly content, highlighting critical areas where even leading AI companies can improve their discoverability.
A full 80% of websites do not provide complete JSON-LD or Schema markup.
Roughly three-quarters of websites fail readability metrics or omit essential alt-text on images.
Many websites rely on heavy visuals but light semantics, which prevents AI systems from parsing them effectively.

Success Patterns

Top performers demonstrated that AI companies with strong technical foundations tend to excel in multiple categories simultaneously, suggesting that a holistic approach yields the best results.
The highest-scoring websites achieve near-perfect results for speed and HTTP hygiene, ensuring fast, reliable indexing.
Consistently rich JSON-LD and meta tags — Open Graph tags and Twitter cards — substantially improves scores.
A clear heading hierarchy combined with FAQ or step-by-step blocks drives up the Answer-Friendly score.

Methodology

We used our tool AI Page Ready to evaluate how well websites can be discovered, understood, and cited by AI systems and large language models. Each company was scored across six critical categories:

Discoverability

Assesses foundational signals (like robots.txt and sitemaps) that enable AI crawlers to find and index your pages. We check for robots.txt rules, presence and syntax of sitemap.xml, HTTP status hygiene, OpenGraph Tags, Twitter Cards Tags, llms.txt and MCP endpoint.

Structured Data

Checks for structured data like JSON-LD Schema and meta tags that translates your content into a logical format for AI agents. We check for JSON-LD Schema, Meta Title and Description, Entity Linking (`sameAs`, Wikidata IDs), Date markup in articles, and Media semantics.

LLM-Friendly Formatting

Checks use of proper headings, FAQs, lists, and tables that allow LLMs to easily parse and extract information.

Accessibility

Checks that key content renders without JavaScript and that core web vitals are healthy.

Readability

Measures how easily your content can be understood by both humans and AI models to avoid ambiguity. Checks in this category include the Flesch-Kincaid score, SMOG score, and content density (real content vs noise).

LLM as a Judge

Uses Gemini to assess how well the page answers high-intent real user questions. We check for embeddings overlap of user questions with the page content and use LLM as-a-judge to gauge content clarity.
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