New research from Evoke Strategy
The 2026 Florida Manufacturing AI Visibility Report
A buyer-perspective study of how AI platforms surface Florida manufacturers before a company is searched by name.
The real test is whether a company appears when buyers search by need, capability, region, or category.
Being searchable by name is not the same as being discoverable by buyers. The more important question is what happens before a buyer knows which companies to consider.
Report at a Glance
Evoke Strategy’s 2026 Florida Manufacturing AI Visibility Report examines how ChatGPT, Gemini, Claude, and Perplexity surface Florida manufacturers before a company is searched by name.
The study analyzed 70 buyer discovery prompts, 280 AI responses, and 877 counted mentions to understand which companies and organizations appear when buyers search by need, capability, region, or manufacturing category.
The report found that AI-assisted buyer discovery is concentrated, platform-dependent, and not always aligned with real-world company scale. In other words, being searchable by name is not the same as being discoverable by buyers.
Three Things Stood Out
AI platforms do not behave like traditional search tools. The study shows that AI discovery narrows the field quickly, real-world size does not guarantee visibility, and Florida relevance is more complex than a headquarters address.
AI discovery narrowed fast
Across the study, AI platforms mentioned 54 different companies or organizations. But those mentions were not evenly distributed. More than half of all recommendations went to just 10 entities, capturing 57.7% of all mentions, while the top 20 captured 80.0%.
That does not mean those companies are the only qualified manufacturers. It means AI-assisted discovery can narrow a buyer’s field before many relevant companies are ever considered.
Size did not guarantee visibility
Twelve companies reviewed within the manufacturing categories did not appear in a single tested response. Based on estimated data, those missing companies represent roughly $8.0 billion in combined estimated revenue.
Five were at or above $500 million, and two were at or above $2 billion. Real-world scale and AI visibility are not the same thing.
Florida relevance was strong, but not simple
Florida-based or Florida-significant manufacturers received 75.7% of all mentions. Another 19.8% of mentions went to companies headquartered elsewhere but with meaningful Florida operations.
That distinction matters because AI tools may surface companies that are relevant to Florida manufacturing without always separating headquarters location from operational footprint.
Four Platforms. Different Discovery Patterns.
The platforms did not behave the same way. For manufacturers, that means AI visibility is not a single outcome. It depends partly on which system a buyer uses to build their early list.
The patterns below summarize what appeared across the report dataset. They should be read as directional platform behavior, not as a claim that every response from each system works the same way in every context.
ChatGPT
138 mentions | 29 unique companies
ChatGPT surfaced the most selective set of companies and organizations. Its responses tended to compress the field into a smaller group of recurring names.
Claude
262 mentions | 30 unique companies
Claude generated the highest mention volume, but those mentions were concentrated across a relatively tight group of companies and organizations.
Gemini
234 mentions | 42 unique companies
Gemini surfaced a broader set of companies and organizations than ChatGPT or Claude. That broader distribution is consistent with a more expansive discovery pattern in the dataset.
Perplexity
243 mentions | 45 unique companies
Perplexity surfaced the broadest unique set of companies and organizations, with the least concentration among the platforms tested.
The Data Behind the Findings: How We Conducted this Study
buyer discovery prompts
AI responses analyzed
company and organization mentions
companies and organizations surfaced
Visibility Share by Manufacturing Category
For category-level analysis, the report focuses on 868 sector-specific mentions across six primary categories. Aerospace & Defense generated the largest share of category-level mentions, followed by Medical Devices, Food, Beverage & Nutrition, Electronics, Building Products & Materials, and Specialty Chemicals & Materials.
Why This Matters for Florida Manufacturers
AI platforms are becoming part of the early research process for buyers, investors, procurement managers, and category researchers.
The challenge is no longer only whether someone can locate your website after searching your exact name. The real test is whether your company appears when buyers search by need, region, capability, or sourcing priority before they know who you are.
What the Report Covers
- What AI platforms surface in response to manufacturing discovery queries
- How concentrated visibility is across regional companies
- Where visibility gaps appear among sizable manufacturers
- How platform behavior differs across ChatGPT, Gemini, Claude, and Perplexity
- What manufacturers can adjust to improve category clarity
Research methodology and public reporting note: This study analyzes aggregate AI visibility patterns across 70 buyer discovery prompts and 280 model responses. Evoke Strategy does not publish a company-level leaderboard or reproduce raw AI model responses verbatim. Named company-level detail was used strictly for internal classification, quality assurance, and private strategic validation, while public documentation focuses on aggregate findings.
Request the Florida Manufacturing AI Visibility Report
Get the complete report to understand how AI platforms shape buyer discovery in Florida manufacturing, where visibility gaps appear, and what manufacturers can do to improve category clarity.
Want to know whether buyers can discover your company through AI?
Find out whether buyers can discover you when they build supplier lists. Request a structured AI Visibility Review from Evoke Strategy to understand where you appear, where gaps exist, and what your team can improve.
1. The Discovery Test
We test how your company appears across relevant buyer discovery prompts in ChatGPT, Gemini, Claude, and Perplexity.
2. Peer Benchmark Profile
See how your visibility compares with relevant category patterns, including where competitors or adjacent companies are being surfaced more often.
3. Diagnostic Briefing
Receive a plain-English roadmap showing where category signals are weak, where gaps appear, and which content steps should come next.
Frequently Asked Questions
A few notes on what the report measures, how the study was conducted, and why AI visibility matters for manufacturers.
What is the Florida Manufacturing AI Visibility Report?
The Florida Manufacturing AI Visibility Report is a buyer-perspective study from Evoke Strategy that analyzes how major AI platforms surface Florida manufacturers in response to unbranded discovery prompts.
What are buyer discovery prompts?
Buyer discovery prompts are unbranded questions that reflect how someone might use AI to identify suppliers, compare regional options, understand category leaders, or build an early shortlist before they know which companies to search by name.
Which AI platforms were included?
The study reviewed responses from ChatGPT, Gemini, Claude, and Perplexity.
What did the study measure?
The study measured AI discovery visibility. It counted which companies and organizations appeared in AI-generated responses across 70 buyer discovery prompts and 280 model responses.
Is this a ranking of Florida manufacturers?
No. The report does not rank companies by quality, revenue, market share, operating performance, or customer satisfaction. It measures how often companies and organizations appeared in the tested AI responses.
Why does this matter for manufacturers?
AI platforms are becoming part of the early research process for buyers, investors, procurement teams, and category researchers. Manufacturers need to understand whether they appear when buyers search by need, capability, region, or category before they know which companies to search by name.
How can a manufacturer improve AI visibility?
Manufacturers can improve AI visibility by clarifying category language, strengthening public capability pages, making location and operating footprint information easier to understand, improving third-party validation, and testing whether they appear in unbranded buyer discovery prompts.



