The source of information that will become more important to AI search

Part 1How Brands Build Trust & Visibility in AI Search

Roughly 20% of AI search responses contain factual inaccuracies. Alex Sherman, co-founder and CEO of Bluefish, an AI accuracy and visibility platform serving Fortune 500 brands, previously co-founded PromoteIQ, a retail media platform acquired by Microsoft. He outlines a first-party content strategy for closing model knowledge gaps, a systematic diagnostic-and-measurement framework for tracking post-optimization accuracy improvement, and a matrix-organization model for aligning search, content, commerce, and compliance teams around a single agentic marketing mandate. Sherman also details the shift toward structured brand data feeds as the next scalable pathway for influencing how models represent products and services.

Part 2The most common misinformation in AI Search

Part 3The biggest mistake brands make when trying to correct inaccurate information in AI search

Most brands fight AI inaccuracies in the wrong place. Alex Sherman, co-founder and CEO of Bluefish AI and former co-founder of PromoteIQ (acquired by Microsoft), now helps enterprise brands close AI accuracy gaps across search and discovery platforms. He outlines why first-party content and direct data feeds to models outperform third-party correction efforts, how large language models increasingly weight brand-verified information over unverified sources like forum commentary, and the diagnostic framework brands need to identify where their AI accuracy gaps actually originate.