WorkAugust 26, 2026via TechCrunch AI
Google’s Gemini has a branding problem, and so does the rest of AI
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.
Key signals
- Focus: 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
The hook
Nobody is talking about how confusing AI product names are hurting adoption. Google's Gemini branding mess is just the symptom.
Consumer AI apps need to stop making users learn their product architecture.