The problem is structural. The big players in artificial intelligence — Google, Microsoft, Anthropic — have built sophisticated technical architectures. However, they have transferred that complexity directly to the end-user, asking them to learn product hierarchies that don't belong to them. Gemini is a model, an app, a pricing plan. At the same time, it's an umbrella brand. The result is disorientation.
This dynamic, analyzed by TechCrunch in an August 2026 article, it doesn't just concern tech giants. In fact, it involves any company that is launching or communicating AI solutions to its audience. In particular, Italian SMEs and mid-market companies risk making the same mistake: communicating the architecture instead of the benefit. Therefore, the topic becomes central for those involved in marketing and digital positioning.
At SHM Studio, we're keeping a close eye on this evolution. AI branding requires a different approach than traditional software. Therefore, those managing communication for products or services with AI components need to rethink their narrative framework. In this analysis, we examine the numbers, causes, and operational implications for Italian marketing managers.
The context: AI has a naming problem, not just a tech problem
August 2026. Google updates the Gemini structure once again. As a result, users find themselves distinguishing between Gemini Advanced, Gemini for Workspace, and the Gemini 1.5 Pro model. Three tiers. One name. Zero perceived clarity.
It is not an isolated case. TechCrunch dedicated a specific analysis to this phenomenon , identifying a recurring pattern in the AI industry. Tech brands build complex product architectures. Then, they communicate them externally without narrative mediation. The consumer—and often even the marketing manager—pays the price in terms of confusion and lack of adoption.
This isn't an aesthetic problem. It's a strategic positioning problem. Furthermore, it has direct implications on the acquisition, retention, and NPS metrics of 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 uniquely communicate what it does and for whom — the so-called brand clarity — is one of the main predictors of adoption in software products. The AI industry is systematically ignoring this principle.
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