Sub-shift
“LOYALTY AUDITS”
Consumers may start choosing assistance according to whose interests it represents.
A retailer can recommend something useful and still prefer the sale that earns it more. Consumers are familiar with that arrangement. The relationship becomes more ambiguous when the same recommendation arrives from an assistant that knows their circumstances and speaks as though it is looking after them.
Accuracy will not settle the question. A recommended product can do everything promised while a cheaper, more suitable or entirely unnecessary alternative goes unmentioned. As people delegate more choices, some will want to understand what shaped the options before trusting the answer.
“LOYALTY AUDITS” is our forecast that these conflicts will influence which services consumers use. They might pay for independent help, compare an assistant’s recommendation elsewhere or stop relying on it in a particular category. Others may knowingly accept a narrower commercial view in return for useful service at a lower price.
The difficult recommendation
A revealing situation is one in which helping the customer costs the provider a sale. Imagine an assistant helping someone prepare for a trip. It could recommend equipment already owned, suggest a repair or conclude that nothing needs buying. That would be a useful test of the relationship.
The point is not to require every retailer to become an independent adviser. A store can serve people well within its own range. The problem arises when the role offered to the consumer sounds broader than the service is prepared to fulfil.
Legal scholar Jack Balkin’s 2016 information-fiduciary argument examined the vulnerability created when people disclose information and rely on digital services they cannot readily inspect. He proposed duties to constrain exploitation of that dependence. His proposed duties are not universal obligations already imposed on assistants. [26]
For consumers, the practical implication is a new distinction between different kinds of help. One service can guide them through a particular shop; another could be paid to represent their interests across providers. The value of that second role grows if the consumer has neither the time nor the knowledge to make the comparison alone.
A business model is only part of the answer
Paying a subscription does not eliminate conflicts. A provider still benefits if the customer keeps paying, and a service funded by advertising can still give sound advice. People need a more useful basis for judgment than free versus paid.
Independent reviewers could test what happens when a request runs against commercial interests. Consumer organizations could compare whether services consider alternatives outside their partnerships. Whether enough people would pay for such checks, or change services because of them, remains uncertain.
For your business, start with the role you are asking the customer to believe you play. If your assistant searches your own range, say so. If you promise a wider comparison, make the exclusions and commercial relationships understandable before the recommendation matters.
An honestly limited service can be valuable. A service that promises to act for the customer has a harder job: its decisions have to support that promise when the convenient answer for the business is different.
THE SOURCE NOTESFollow the thinking 1 source · what they show and where their limits lie
Sources and further reading
These sources inform the article. A product announcement describes an offer, not how widely people use it. Arguments and imagined futures are kept separate from observed results.
Balkin proposes duties suited to particular information relationships. This is not a statement that every digital provider currently has the same fiduciary obligations as a professional adviser.
About this research edition
This article draws on selected sources and our interpretation of their implications for consumers. The wider collection contains 50 articles and original illustrations. We have not read everything by everyone on the reading list, calculated the probability of each future or established worldwide adoption. The collection is not exhaustive.
The illustrations are AI-generated, with a visual approach informed by TrendWatching’s 2024 and 2025 reports. They depict ideas rather than observed events. If an article’s central idea changes, its image needs another look. Small edits need not mean a new illustration; automatic replacement is not active.
Each innovation has a source, a review date and an explanation of its relevance and limits. Some are early signs of the change; others offer a useful comparison. None proves the forecast. Monthly monitoring and automatic selection of new examples are not running.