When AI Gets You Wrong: Identity, Ambiguity & Who Controls the Answer

What happens when AI knows your name—but doesn't actually know who you are?

In this roundtable episode of the AI Visibility Podcast, Jason T Wade is joined by Jason Barnard, Jodi Koch, and Su Belagodu for a wide-ranging conversation about identity, ambiguity, trust, human judgment, and the growing influence of AI recommendations.

Jason Barnard starts with one of the fundamental problems of AI visibility: entity ambiguity. People share names, companies have inconsistent descriptions, and AI systems have to decide which facts belong to which entity. Su shares her own example of AI incorrectly attributing a Dubai speaking appearance to her because it confused her with another person working in AI governance. Roundtable on AI, Identity, and Ambiguity.docxDOCX Roundtable on AI, Identity, and Ambiguity.docxDOCX

The discussion moves into a larger question: if Google once gave users ten links to evaluate, what changes when an AI system increasingly makes the recommendation itself?

Jason Barnard argues that businesses need to deliberately educate AI systems about who they are, what they do, and who they serve. Su adds an important counterpoint: AI outputs remain probabilistic, and human judgment still matters—especially when agents and automated systems begin making decisions at scale. Roundtable on AI, Identity, and Ambiguity.docxDOCX

Jodi brings the conversation into the physical world. As an interior designer with more than two decades of experience, she uses AI to rapidly visualize ideas with clients—but points out that an AI-generated room can still ignore structural reality. The technology can accelerate the process, but it does not replace the experience required to know whether the proposed design actually works. Roundtable on AI, Identity, and Ambiguity.docxDOCX

A recurring theme emerges: AI visibility begins with being correctly understood. If a machine cannot reliably resolve who you are, it cannot reliably evaluate, recommend, or select you.

• Name and entity ambiguity
• What AI gets right—and wrong—about people
• Correcting machine-generated identity errors
• Digital consistency and corroborating sources
• AI as recommender instead of search engine
• Probabilistic AI outputs
• Human-in-the-loop systems
• AI agents and automation
• Using AI in interior design
• Trusting versus verifying AI output
• Personal brands and company brands
• Controlling how AI understands an entity
• Why human expertise becomes more important alongside AI

Jason Barnard is founder and CEO of Kalicube, a digital brand engineering company focused on helping people and companies control how Google and AI systems understand and represent them. His work spans entity identity, Knowledge Panels, digital brand intelligence, and AI-era recommendation systems. Kalicube - Digital Brand Engineers

Jodi Koch is the founder of Elizabeth Erin Designs and host of the Designing in 5D podcast. A nationally recognized interior designer with more than two decades of experience, she works with homeowners, investors, and hospitality clients using her Designing in 5D process. Elizabeth Erin Designs

Su Belagodu is an AI adoption and executive advisor and creator of the HITL Maturity Model™. Her work focuses on designing AI systems with meaningful human oversight, helping organizations move AI projects into production, and determining where humans need to remain in the loop. Sublagodu

Jason T Wade is an AI Visibility Architect and founder of BackTier. His work focuses on how AI systems discover, resolve, understand, cite, include, and recommend people, companies, products, and ideas. He is the host of the AI Visibility Podcast. Jason AI Wade

Jason Barnard / Kalicube
Kalicube.com
Jason Barnard Bio

Jodi Koch / Elizabeth Erin Designs
Elizabeth Erin Designs
Designing in 5D Podcast

Su Belagodu
SuBelagodu.me
Su Belagodu on LinkedIn

Jason T Wade
JasonWade.com
BackTier