For decades, marketing has been built around a relatively simple premise: consumers make choices, and brands compete to influence them. A need arises, a handful of brands come to mind, and the consumer narrows or widens that set as they gather information before settling on one. While specifics differ by category, this underlying process has remained remarkably consistent, and much of marketing strategy is about ensuring a brand is present and distinctive at key stages of this journey. But is this all about to change? As agentic AI systems become capable of interpreting needs, evaluating options, and acting on behalf of consumers, choice becomes less an act of human judgement and more an optimisation process, which may have profound implications for brands.
Historically, brands have functioned as mental shortcuts. Faced with complexity and uncertainty, consumers use what they know about a brand to simplify decisions and reduce perceived risk. AI doesn't necessarily need those shortcuts. An agent can evaluate structured signals such as performance, reliability, compatibility, and reputation, compare hundreds of options in seconds, then recommend the one it believes best meets the consumer's needs. Brand doesn't become irrelevant in that world, but it starts to matter in different ways.
To understand where this shift is heading, we interviewed 1,000 Australians about their recent purchases across a range of categories. The results suggest AI adoption for purchasing is still at an early stage, but the trajectory is clear.
Almost half (49%) claim to have used AI as part of a purchase journey and 63% plan to in future. Use is higher amongst younger Australians (67% for 18 to 34s) and significantly lower among older Australians (28% for those 55+). It shows up more in categories where the stakes are higher, such as vehicle purchases, holidays, and electronics, and less in habitual, low-effort categories like groceries. Only 6% let it make the purchase; the real action is earlier on in the journey, where the consideration set forms and brands conventionally do most of their work. So, people still buy, but for some the shortlist they buy from is increasingly drafted by a model. Trust is a key barrier: 90% of those who have used AI in a purchase journey say they verify the AI-generated information through other sources.
So what does this mean for brands? The first implication is that brand still matters. Consumers remain heavily involved in purchase journeys and even when AI is used, existing experiences, preferences, and mental shortcuts shape the interaction. A prompt is rarely neutral; it reflects what people already know, want, and believe. Furthermore, AI is not brand blind. If anything, it may be brand obsessed. AI systems draw on a vast ecosystem of information: brand websites, reviews, expert commentary, publications, forums, and consumer discussion. Brands that are well-established, well-documented, and consistently associated with relevant attributes have more signals for AI to interpret.
This creates an additional competitive battleground. For decades, marketers have focused on share of mind. Increasingly, they may need to think about share of model: the extent to which a brand is visible, understood and recommended within AI-generated responses. In a more AI-mediated world, what others say about a brand becomes increasingly important. Reviews, expert commentary, independent publications, retailer listings, spec sheets, forum threads, and whether all of it tells the same story. All of these become potential inputs into the models ultimately influencing consumer decisions.
The implication is not that marketers should abandon traditional brand building. Quite the opposite. Brands will still need to build awareness, distinctiveness, and differentiation among humans. But they will increasingly need to ensure that the broader information ecosystem represents them accurately, consistently, and favourably to machines. The next generation of brand competition will not simply be about winning the consumer's consideration set. It will also be about winning the algorithm's.
James Jayesuria, Partner & Managing Director, Sydney, Nature
Alex Coningham, Senior Associate Director & Head of AI, Nature
