Google’s Gemini has a branding problem, and so does the rest of AI
Nobody is talking about how confusing AI product names are hurting adoption. Google's Gemini branding mess is just the symptom.
Why it matters
Consumer and enterprise AI products suffer from poor naming and positioning that forces users to understand model architecture instead of just using the tool. This is a barrier to mainstream adoption and a UX/go-to-market problem the industry hasn't solved.
The key facts
8 to knowFocus: consumer AI app branding and UX friction
Example cited: Google Gemini's confusing positioning across models and tiers
Industry-wide pattern: technical names obscure product value
Implication: adoption friction from poor product naming strategy
Gemini branding fragmentation (Gemini 1.5, 2.0, Flash, Pro, Ultra across contexts)
Consumer AI UX problem: users forced to understand model selection/versioning
Industry-wide pattern: ChatGPT tiers, Claude model selection, competing mental models
Adoption friction in enterprise/consumer workflows from unclear product positioning
Go to the source
TechCrunch AItechcrunch.com
Publisher excerpt: Consumer AI apps need to stop making users learn their product architecture.