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The design of an AI shopping assistant can shape whether consumers trust it.

Studies of AI shopping assistants, chatbots and recommender systems associate consumer trust with characteristics of the AI interface itself, alongside the brand or retailer behind it.

Signal 012 · Open Signal · First observed Identified October 2026 · Last reflected 7 October 2026

Studies of AI shopping assistants, chatbots and recommender systems associate consumer trust with characteristics of the AI interface itself, alongside the brand or retailer behind it.

What we see

  • In a study of generative-AI marketing communication, human-like design (anthropomorphism) was associated with higher purchase intention, in interplay with transparency.
  • Transparency about how a system works, including explaining its recommendations, was identified as a determinant of trust in AI chatbots and in AI recommender systems.
  • In a study of online shopping assistants, trust mediated the relationship between the assistant's perceived attributes and consumers' intention to accept it.

Why it matters

These studies measure perceptions and intentions at one point in time. Within those limits, they suggest the AI interface takes part in how trust in a commercial relationship is formed, rather than acting as a neutral channel.

Cralgo reflection

We read this as a question of design responsibility as much as interface quality: the system between a customer and a product carries part of the trust relationship.

What these studies cannot yet show is how that trust behaves over time, or whether it transfers to the brand or seller behind the system.

Questions being explored

  • If consumer trust is mediated by an AI, how should a brand's own voice and values be represented through that system?
  • What new forms of product information and data are needed for products to be discoverable and well-represented by AI agents?
  • As AI mediators become more sophisticated, how does a consumer distinguish between an objective recommendation and a sponsored placement?
  • What are the long-term effects on brand loyalty when the primary discovery relationship is with a platform's AI rather than the brand itself?

References

All Signals

We identify emerging patterns and opportunities through research and Signals, and take them into real-world application through technology strategy and leadership, AI and data, digital commerce and consumer platforms, product and engineering, and technology-led growth and transformation.

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Where we apply this thinking

Technology Strategy & Leadership · AI & Data · Digital Commerce · Consumer Platforms · Product & Engineering · Technology-led Growth & Transformation

Psychology × Technology × Organisations → Outcomes — the research lens Cralgo explores through.

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Founding

Cralgo was founded in 2025 by Anil Kabir Kumar. Legal entity: Cralgo Innovations (OPC) Private Limited, incorporated 27 June 2025.

The three lenses

Psychology — how people perceive, decide and behave. Technology — what the system makes possible or constrains. Organisations — what conditions shape action. Outcomes emerge from their interaction.

Research — the questions underneath the work

Collaborative investigation with organisations, universities, practitioners and the people a question affects. Commissioned research is disclosed as such.

Beyond — questions Cralgo carries on its own account

Beyond describes the origin of a question: one Cralgo carries independently, or around a public-purpose context.

Working together — the belief behind all of it

Listening before concluding, room for different perspectives, useful disagreement, and evidence that still matters.