Buyers do not want “more AI”. They want less work, fewer dead ends, and more control. That is the finding from Prophet’s study of 2,000 consumers.
This research is particularly useful because it moves the conversation away from AI spectacle and towards customer utility. Buyer adoption is rising, but confidence and emotional warmth are not. Trust, transparency and human connection emerged as recurring concerns.
Many marketers are still speaking as if AI is interesting in itself. It is not. Not to buyers who have already passed the novelty stage. They are asking a more practical question: will this help me get something done, with less friction, less doubt and less wasted time? In plain terms, they are not just asking AI to answer questions. They want it to compare options, manage tasks, make recommendations and execute decisions.
Brand touchpoints are shifting
Buyers may still love the brand. But increasingly, the first conversation may happen somewhere else. It may happen inside a personal AI assistant, a comparison layer, a shopping agent, a calendar, a bank app, a travel planner or a replenishment service. The brand’s website, campaign, email or app may not be the starting point. It may not even be visible.
That is the first provocation for marketers. If the customer delegates more of the journey to AI, brand preference is no longer built only through persuasion. It is also built through usefulness, clarity and machine-readable evidence.
A buyer asking AI to monitor discounts is not asking to be engaged. They are asking to be protected from overpaying. A buyer asking AI to prevent customer service problems is not asking for a warmer chatbot. They are asking the brand to eliminate the need for any service interaction. A buyer asking for automatic needs-based purchasing is not browsing. They are outsourcing low-interest decisions.
From content production to buyer burden reduction
We have moved from “How can marketers use AI to create more content?” to “How can marketers use AI to reduce customer burden?”
Too much current AI marketing work is supply-side thinking. It helps the brand produce faster. Faster copy. Faster images. Faster segmentation. Faster campaign testing. Those things may matter operationally. But they do not automatically create customer value. They may simply increase the volume of mediocre interaction.
This research points to a demand-side shift. Buyers are asking for AI that acts on their behalf. They want screening, summarisation, coordination, negotiation and prevention. In that world, the marketer’s job becomes less about filling channels and more about becoming a trusted input into the customer’s decision system.
Trust has become an operational imperative
This has practical implications.
First, brand data must become cleaner, more complete and easier for AI agents to interpret. If an AI tool is comparing products, prices, availability, policies, reviews, sustainability claims or service terms, vague brand language will not help. The winning brand may be the one that provides the clearest evidence.
Second, marketers need to stop treating trust as a tone-of-voice problem. Trust in an agentic environment is operational. Can the customer’s AI understand the offer? Can it verify the claim? Can it find the returns policy? Can it compare the total cost? Can it book, cancel, reorder or escalate without friction? If not, the brand has a trust problem, however warm the campaign language may be.
Third, “human-centred AI” needs to be rescued from cliché. We need to define what the phrase means in practice. Does it mean fewer unnecessary prompts? Clearer consent? Better handoffs to humans? More explainable recommendations? Less manipulation? Better accessibility for older users? More control for the customer? Without an operational definition, human-centred AI becomes a slogan.
Finally, there is no single AI-enabled consumer segment. Marketers supporting a broad buyer base should not design one generic AI layer and declare the work done. Some buyers may want assistance. Some want speed. Some want reassurance. Some want autonomy. Some want proof. Some want a human exit route.
Thought leadership to adapt to agentic buyer journeys
In many ways, experts are becoming critical translators between AI systems, marketers and buyer expectations. Your role is no longer just explaining tools. It is helping brands understand how customers will interact with AI-driven decision systems.
As buyers increasingly rely on AI agents to compare and filter choices, brands must compete for inclusion in the agent’s shortlist. Awareness and emotional appeal still matter, but brands also need structured, retrievable and executable information that AI systems can process.
The real opportunity is not using AI to say more. It is to help customers decide faster, act with confidence and feel less burdened by complexity.