What Auditing 500 Manufacturers Reveals About AI Visibility
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For more information contact Brooke Babcock
Every manufacturer wants to know whether AI tools like ChatGPT, Gemini, and Perplexity will recommend them, or even recognize them correctly. Almost nobody has actually measured it. So we audited 500+ U.S. manufacturers, scoring each company on a four-part model—entity identity, authority, trust signals, and digital infrastructure—then ran over 100,000 niche-aware queries across five major AI platforms.
This session presents what we found: where manufacturers cluster on AI readiness, what separates the companies AI cites from the ones it doesn’t, and which widely-held assumptions the data complicates. No hype and no acronym soup. Just original data, an audit you can run on your own company, and what to do Monday morning.
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Ian Wilson
As Co-Founder and designated jack-of-all-trades at B2B marketing agency build/create, Ian Wilson brings 15+ years of experience working at the intersection of design, web development, and digital marketing. When AI models started answering the questions buyers used to bring to Google, Ian went looking for evidence rather than opinions, launching original research into how AI platforms recognize, describe, and recommend U.S. manufacturers. A thoughtful and energizing speaker, he brings creative vision grounded in nuts-and-bolts practicality, and a healthy skepticism of anything that sounds like a silver bullet.
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Eric Lynch
Eric Lynch co-founded build/create with Ian in 2010 and leads Rev Ops for the agency, helping business leaders connect brand and marketing strategy to how their companies actually make money. A business owner himself, he starts with the P&L rather than the creative brief. In this research, he's the one asking the uncomfortable question: whether AI visibility translates into pipeline, or just into a flattering dashboard. Clients know him for getting past the noise to the problem underneath.
