CRM Software leads AI visibility at 32.0 average score. AI Agent Platforms average 1.5. I broke down the 2,014-company dataset by industry. The first finding is not about which industry wins. It is about how fragmented the data is.
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The Fragmentation Problem
Before the leaderboard, a caveat. The 2,014 companies in our dataset span 1,587 unique industries. That is not a typo.
| Industry Size | Companies | Industries |
|---|---|---|
| 10+ companies | 53 | 4 |
| 5-9 companies | 125 | 21 |
| 3-4 companies | 187 | 58 |
| 1-2 companies (long tail) | 1,649 | 1,504 |
81.9% of companies are in industries with only 1-2 data points. That means most industry-level benchmarks are statistically unreliable. I am showing the data anyway because directional patterns still matter. But treat small-sample industries with the skepticism they deserve.
The Industry Leaderboard (5+ Companies)
Here are the 25 industries with at least 5 companies in the dataset, ranked by average AI visibility:
| Industry | Companies | Avg AI Visibility | Avg Brand Authority | Avg GEO Score |
|---|---|---|---|---|
| CRM Software | 5 | 32.0 | 92.2 | 71.2 |
| Customer Data Platforms | 6 | 18.8 | 57.3 | 58.7 |
| Customer Service Software | 5 | 13.4 | 67.6 | 72.0 |
| Customer Engagement Platforms | 8 | 12.5 | 50.0 | 61.9 |
| Contact Center Software | 10 | 10.7 | 41.5 | 69.2 |
| Contract Management Software | 7 | 10.4 | 43.9 | 55.6 |
| Application Security Tools | 6 | 8.8 | 24.7 | 61.8 |
| Influencer Marketing Platforms | 6 | 8.8 | 64.5 | 54.5 |
| Conversational AI Platforms | 9 | 8.1 | 61.3 | 60.7 |
| Learning Management Systems | 5 | 8.0 | 18.2 | 66.0 |
| Business Intelligence Tools | 6 | 7.8 | 49.0 | 62.8 |
| Identity Verification Services | 5 | 5.4 | 35.6 | 67.0 |
| FP&A Software | 6 | 4.5 | 37.2 | 62.5 |
| Browser Automation Tools | 5 | 4.0 | 25.4 | 57.4 |
| Procurement Software | 5 | 4.0 | 35.4 | 64.4 |
| Enterprise AI Platforms | 10 | 2.7 | 55.5 | 55.0 |
| AI Agent Platforms | 22 | 1.5 | 29.0 | 56.5 |
| Ecommerce Platforms | 5 | 1.4 | 34.6 | 58.4 |
| Field Service Management Software | 6 | 1.2 | 37.2 | 48.8 |
| Workflow Automation Tools | 6 | 0.0 | 62.3 | 55.5 |
| Observability Tools | 5 | 0.0 | 33.0 | 51.0 |
| Customer Support Software | 6 | 0.0 | 36.2 | 65.3 |
| Software Development Services | 7 | 0.0 | 45.6 | 66.6 |
| Custom Software Development Services | 6 | 0.0 | 11.3 | 52.0 |
| Technology | 11 | 0.0 | 14.3 | 14.8 |
The range is extreme: 32.0 to 0.0. Six industries with 5+ companies have zero average AI visibility.
Finding #1: Established Categories Win
The top 5 industries are all well-defined, mature software categories: CRM, CDP, customer service, customer engagement, contact center. These are categories that AI models have been trained on extensively. The training data contains thousands of articles comparing CRMs, reviewing customer service tools, and listing CDPs.
This makes sense. AI models recommend what they have seen recommended before. If your category has decades of review content, comparison articles, and analyst reports, the models have a large pool of evidence to draw from. Newer categories (AI Agent Platforms, Browser Automation Tools) don't have that history yet.
Finding #2: Brand Authority Matters More Than Industry
CRM Software has the highest visibility (32.0) and the highest brand authority (92.2). But look at the anomalies:
| Industry | Avg Authority | Avg Visibility | The Pattern |
|---|---|---|---|
| CRM Software | 92.2 | 32.0 | High authority, high visibility |
| Influencer Marketing Platforms | 64.5 | 8.8 | High authority, moderate visibility |
| Workflow Automation Tools | 62.3 | 0.0 | High authority, zero visibility |
| Conversational AI Platforms | 61.3 | 8.1 | High authority, moderate visibility |
| Enterprise AI Platforms | 55.5 | 2.7 | High authority, low visibility |
Workflow Automation Tools averages 62.3 brand authority and 0.0 AI visibility. Enterprise AI Platforms averages 55.5 authority and only 2.7 visibility. High brand authority is necessary but not sufficient. You also need the category itself to be one that AI models discuss and recommend.
This matches what I found in the brand authority analysis: brand authority is the strongest predictor across the full dataset. But within niche categories, the category's training data coverage matters too.
Finding #3: GEO Scores Don't Separate Winners from Losers
The GEO score column tells a now-familiar story:
| Visibility Tier | Avg GEO Score |
|---|---|
| Top 5 industries (10.7-32.0 visibility) | 66.6 |
| Bottom 5 industries (0.0 visibility) | 49.9 |
| Middle industries (1.2-8.8 visibility) | 58.4 |
The GEO difference between the top and bottom is small (66.6 vs 49.9). Some zero-visibility industries have GEO scores above 60. Software Development Services has an average GEO of 66.6 and zero AI visibility. Customer Support Software has a GEO of 65.3 and zero visibility.
GEO is a hygiene factor. It does not determine whether AI recommends your industry.
Finding #4: AI Agent Platforms Are Ironically Invisible
The largest industry cluster in the dataset is AI Agent Platforms with 22 companies. Their average AI visibility is 1.5. The companies building AI tools are, on average, invisible to AI.
This is not as ironic as it sounds. The AI agent space is new, fragmented, and moves fast. There are not yet hundreds of comparison articles and analyst reviews for AI agent platforms. The training data has not caught up to the market.
If you are in this space, this is actually a window. The category is large enough to matter (22 companies just in our dataset), but visibility is low enough that early movers can establish category leadership before the training data solidifies.
Finding #5: The 77.5% Zero Problem
Across all 2,014 companies, 77.5% score exactly zero on AI visibility. This is even starker than the 85.7% in the 0-20 tier because it isolates the true zeros.
| Visibility | Companies | % |
|---|---|---|
| Exactly 0 | 1,560 | 77.5% |
| 1-20 | 166 | 8.2% |
| 21-40 | 115 | 5.7% |
| 41-60 | 46 | 2.3% |
| 61-80 | 41 | 2.0% |
| 81-100 | 86 | 4.3% |
This is the distribution that the 85-5 rule describes: a small group at the top, a massive group at zero, and almost nothing in between.
What This Means for Your Strategy
If you are in an established category (CRM, customer service, business intelligence): the opportunity is clear. AI models already discuss your space. Your job is to build enough brand authority to be in the consideration set. Third-party reviews, Reddit presence, Wikipedia, and consistent category language will move the needle.
If you are in an emerging category (AI agents, browser automation, workflow tools): AI models do not yet have strong opinions about your space. You have a window to define the category. Publish the comparison content. Seed the review sites. Be the reference that models find when the training data updates.
If your category is generic ("Technology," "Software Development Services"): redefine your category. AI models cannot recommend you for "technology." They recommend for specific use cases. Pick the most specific category you can defend and build all your content around it.
Honest Limitations
This analysis has clear limitations:
- Small sample sizes. Only 4 industries have 10+ companies. The leaderboard is directional, not definitive.
- Self-selected sample. Companies that run the Loamly check tool are not representative of all businesses. The sample skews toward companies interested in AI visibility.
- Industry labels are self-reported. Some are more specific than others. "Technology" is too broad to be useful. "Contact Center Software" is precise.
- Point-in-time snapshot. AI models update their training data. Industries that are invisible today may not be tomorrow.
I would not bet a strategy on the exact numbers in the leaderboard. I would bet on the patterns: established categories with strong brand authority win, GEO doesn't separate industries, and 77.5% of companies score zero regardless of sector.
Methodology
Data source: 2,014 Loamly brand reports (completed as of Feb 15, 2026).
Industry classification: Self-reported by the company during the check process. 1,587 unique industry labels across 2,014 companies.
Metrics: Overall AI visibility (0-100 scale), brand authority score, GEO score. Each report runs 48 queries across ChatGPT, Claude, Gemini, and Perplexity.
Threshold: The leaderboard uses a minimum of 5 companies per industry. At 10+, only 4 industries qualify.
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Last updated: February 16, 2026
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