Accenture's 2026 Consumer Pulse Research, drawing on 25,590 respondents across 16 countries, confirms something that has been building quietly for two years: consumers are ready to let software handle the parts of shopping they find tedious.
The numbers tell a layered story. Nearly three quarters of respondents would let an AI agent handle routine tasks such as finding deals, renewing subscriptions, or reordering familiar products. About a third would go further and let an agent choose the best available option for them, within limits they set themselves, like a budget cap or a preferred brand list, then review and approve before payment goes through. Only 9% are ready to let an agent complete a purchase without that final check.
So full autonomy is still a small minority position. But that framing misses the more important point. Even the 74% who delegate only the routine tasks are already creating a major commercial problem for brands and sellers.
Here is why. When a consumer uses an AI agent to shop, the agent does not visit your website, respond to your advertising, or read your brand story. It reads structured data: price, stock levels, delivery time, return policy, product specifications. If that information is missing, vague, or hard for a machine to parse, the agent either skips your product entirely or ranks it lower than a competitor with cleaner data. Research on Google's AI shopping tools found that products with complete data attributes see three to four times higher visibility in AI recommendations than those with sparse information.
This is a quiet shift in how competitive advantage works. For years, businesses invested in brand awareness, web design, and content marketing to win customers. Those tools still matter for the roughly 31% of consumers who, per the Accenture data, believe physical stores and direct brand experiences will become more important, not less. But for the growing share of purchasing that runs through an agent, the deciding factor is data quality, not brand prestige.
The brand loyalty question is where this gets uncomfortable. The survey found that 37% of consumers who describe themselves as brand-loyal would still allow an agent to switch brands if the agent found a better fit on price, availability, or service. Deloitte, in a separate study, found that 81% of retail executives already expect AI to weaken brand loyalty by 2027. That alignment between consumer data and executive concern is not coincidental.
Consumers are not abandoning preferences. They are outsourcing the effort of acting on them. A person who cares about healthy food still wants healthy food. They just no longer want to spend time comparing labels and prices. If their agent can do that reliably, within the rules the consumer has set, most people are fine with it. The Accenture data confirms this: 63% of consumers said they want an agent that helps them shop for a better version of themselves, making healthier choices or staying within budget.
The practical consequence for any business that sells to consumers, whether that is insurance policies, holiday packages, telecoms contracts, or groceries, is that product and service information needs to work for machines, not just people. Pricing needs to be current and accurate. Policies need to be readable in a standard format. Availability, delivery terms, and service conditions all need to be consistently structured and up to date. This is not a technology project. It is a data discipline and operations question.
The businesses most at risk are those that have relied on brand recognition or customer inertia to hold market share without maintaining the underlying operational data that an agent would use to evaluate them. A well-known name in a product category is worth nothing if the agent cannot read your stock levels or parse your returns policy.
At the same time, the Accenture data points to categories where human preference holds firm. Travel, clothing, and lifestyle purchases showed a sharp drop in willingness to delegate as the level of autonomy increased. Consumers still want to choose the hotel room. They want to pick the outfit. These are areas tied to identity and personal enjoyment, where the agent can help with logistics but not replace the decision itself.
The picture that emerges is selective delegation, not wholesale automation. Consumers are using agents the way busy people have always used trusted advisors: handle the paperwork, find the options, do the comparison, but let me make the call on anything that actually matters to me. The businesses that understand which side of that line their products sit on, and prepare their data and operations accordingly, will hold their position. Those that wait for the pattern to become obvious before acting are already behind.