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AI is shifting from a creative tool to a decision-making infrastructure, and synthetic people (avatars, mascots, digital twins) are becoming the new interface for brand-consumer interaction and testing

Executive summary: Il Sole 24 Ore published an analysis of how AI is evolving from a creative tool into a decision-making infrastructure, enabling new models of testing, relationships and interaction between brands and consumers through synthetic people such as avatars, mascots and digital twins. The shift positions AI as a core business infrastructure rather than an add-on, with implications for how companies test products, manage brand relationships and allocate capital toward AI-driven customer engagement.

Who is involved: Brands and consumers are the primary actors, with AI vendors and technology platforms enabling synthetic people; the article is published by Il Sole 24 Ore, an Italian business newspaper.

Likely next (inference): More companies are expected to pilot synthetic-person use cases in marketing, customer service and product testing, with a growing focus on the reliability and governance of AI-driven decision-making.

The article describes how AI is evolving beyond content generation into an infrastructure layer that supports decision-making, enabling new models of testing, relationships and interaction between brands and consumers. Synthetic people — avatars, mascots and digital twins — are presented as a concrete application of this shift. The implication is that companies are beginning to treat AI not as a novelty but as a core operational asset for customer engagement and product validation.

What's next — scenarios

Inference: scenarios and probabilities are Beyond's assessment, not reported fact.

Base: Synthetic people become a standard marketing/test layer (55%)

Brands in retail, events and telecom adopt avatars and digital twins for customer engagement, driving demand for AI infrastructure and creative tooling.

Upside: AI decision infrastructure accelerates across industries (25%)

Synthetic people expand into high-stakes testing (e.g., product design, training simulations), increasing AI infrastructure spending and creating new compliance needs.

Downside: Consumer or regulatory backlash limits adoption (20%)

Concerns about deceptive AI personas or data use slow adoption, pushing companies to add disclosure labels and human oversight, raising costs.

What to watch

Timeline

Analysis — what this means

Likely next events

Sectors affected

Regulatory implications

Historical parallels

Sources

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