The problem is structural. The big AI players (Google, Microsoft, Anthropic) have built sophisticated technical architectures. But they've passed that complexity straight on to the end user, asking them to learn product hierarchies that mean nothing to them. Gemini is a model, an app, a pricing plan. It's also an umbrella brand. The result is disorientation.
This dynamic, analyzed by TechCrunch in an August 2026 article, doesn't only concern the tech giants. It affects any company launching or presenting AI solutions to its audience. Italian SMEs and mid-market companies in particular risk repeating the same mistake: communicating the architecture instead of the benefit. That makes it a central issue for anyone working in marketing and digital positioning.
At SHM Studio, we follow this evolution closely. AI branding calls for a different approach than traditional software. Anyone managing communication for products or services with AI components needs to rethink their narrative framework. In this analysis, we look at the numbers, the causes and the practical implications for Italian marketing managers.
The context: AI has a naming problem, not just a technology problem
August 2026. Google once again updates the structure of Gemini. Users now have to tell apart Gemini Advanced, Gemini for Workspace and the Gemini 1.5 Pro model. Three levels. One name. Zero perceived clarity.
It's not an isolated case. TechCrunch devoted a dedicated analysis to this phenomenon, identifying a recurring pattern in the AI industry. Tech brands build complex product architectures. Then they present them to the outside world with no narrative mediation. Consumers, and often marketing managers too, pay the price in confusion and low adoption.
This isn't a cosmetic problem. It's a strategic positioning problem. It also has a direct impact on acquisition, retention and NPS for any product with AI components.
The numbers that matter: trust, confusion and adoption
The problem isn't access. It's understanding.
A brand's ability to say clearly what it does and who it's for, known as brand clarity, is one of the strongest predictors of adoption in software products. The AI industry is systematically ignoring this principle.
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