AI Collision: 32 Ways AI Is Getting You Wrong in the New Selection Economy examines how artificial intelligence systems can confuse, misrepresent, overlook, or inaccurately assemble the identities and expertise of individuals, professionals, authors, and organizations. Tamara Patzer identifies 32 distinct “AI collisions,” including identity confusion, semantic hijacking, inaccessible content, inconsistent professional signals, outdated information, missing attribution, category errors, geographic invisibility, and unauthorized assembly of information.

The book introduces the concept of AI identity accuracy and explains how artificial intelligence evaluates machine-readable evidence, source consistency, authority signals, recency, citations, and professional positioning when generating answers or recommending experts.

Each chapter includes a diagnostic prompt that readers can use with major AI platforms to evaluate how accurately their own identity, credentials, work, and authority are represented. The book concludes with corrective strategies, an authority-foundation framework, a 30-day implementation plan, a diagnostic prompt library, and an AI Collision self-assessment.