AI is now the first stop for Australian shoppers-trust decides which brands win

AI is now the first stop for Australian retail decisions

A new study from The Navigators, AI Brandscape 2026, shows that AI sits between consumers and your owned channels. Forty-three percent of Australians now use AI tools regularly, with another 20% having tried them. For many, assistants and AI search summaries guide choices before a website, app, or store gets a look-in.

Dean Harris, Director at The Navigators, says a growing cohort of "AI shoppers" rely on these tools across categories. His core message for brands: learn how trust and visibility are formed inside AI systems, then adjust your marketing so you still show up when it counts.

How Australians use AI before they buy

• Compare brands and options: 80%
• Discover new brands or products: 72%
• Compare or understand prices: 56%
• Get recommendations: 48%
• Find where to buy: 37%

In short, AI is the comparison and confidence layer. If your brand doesn't feed that layer with clear, verifiable information, someone else will.

Where AI has the most pull

Current use by category:

• Electronics and technology: 18%
• Groceries and everyday household items: 14%
• Health products and services: 13%
• Travel and accommodation: 12%
• Home appliances: 11%

Openness to AI-enabled purchasing is strongest in convenience-led retail:

• Groceries and everyday household items: 13%
• Electronics and technology: 12%
• Health products and services: 9%
• Travel & accommodation: 8%
• Restaurants, food delivery & takeout: 8%

Gender patterns worth factoring in

Men are more likely to be regular AI users (50% vs 38% of women), so they'll often see brands via AI earlier in the decision path. Women are more likely to have never used AI (38% vs 30% of men), but among users, women report a broader range of use cases on average.

• Implication: shape early-stage prompts and comparison content for male-skewed audiences.
• Implication: for female users, cover more scenarios and questions with clear, trustworthy answers.

Trust vs attention: the gap to close

Forty-one percent pay attention to AI-generated search summaries, yet only 29% say they trust them. People use the output, but they want proof. Expect AI systems to get stricter about which sources they surface and cite.

Douglas Nicol, co-founder of ACAM, says marketers need to shift focus from back-end automation to how AI reroutes buying behavior. Some brands will need targeted fixes; others, a broader reset of strategy and measurement.

What this means for marketers

1) Make your brand machine-readable

• Use structured data (e.g., Product, FAQ, HowTo). It helps assistants parse specs, prices, availability, policies, and store locations. See Schema.org.
• Create short, scannable summaries for each product and category. AI favors concise, unambiguous facts.

2) Win the comparison request

• Publish "Brand A vs Brand B" pages, spec sheets, and price breakdowns. Include who each option is best for.
• Offer clear tiering (good/better/best) and decision checklists so AI can lift usable logic.

3) Build trust signals AI will cite

• Earn third-party reviews and expert commentary. Align with reviewer guidelines, e.g., the ACCC's guidance on online reviews.
• Publish verifiable claims, certifications, and support content. Avoid vague superlatives; include sources.

4) Keep brand facts current

• Maintain a canonical "About," "Press," and "Facts" page with founders, locations, warranties, returns, and customer service details.
• Update product feeds and change logs. Fresh, consistent data reduces stale answers and miscitation.

5) Prepare for AI search and assistants

• Test common prompts on leading assistants. Note citations, missing data, and hallucinations; fix upstream content.
• Create answer packs: short paragraphs, specs, and FAQs formatted for copy-and-cite.

6) Measurement that fits AI-mediated discovery

• Track "share of assistant" by monitoring how often your brand appears or is cited for key prompts.
• Use proxies: branded search lift, direct traffic around feature launches, referral links from assistants that cite sources.

7) Category plays

• Electronics/appliances: spec comparators, warranty clarity, setup/how-to content.
• Groceries: value swaps, bundle logic, dietary filters, store/stock accuracy.
• Health: evidence summaries, clear safety info, compliant claims, access to professionals where relevant.
• Travel: transparent fees, itinerary builders, cancellation rules, trust markers.

8) Upskill the team

• Train marketers to brief, test, and measure AI-influenced buying paths: AI for Marketing
• Give brand leaders a framework for trust, visibility, and measurement in AI systems: AI Learning Path for Brand Managers

Key stats at a glance

• Regular AI users in Australia: 43% (plus 20% have tried)
• Top uses: compare brands (80%), discover new (72%), price checks (56%), recommendations (48%), where to buy (37%)
• Top categories (current use): electronics (18%), groceries (14%), health (13%), travel (12%), appliances (11%)
• Openness to AI-enabled purchasing: groceries (13%), electronics (12%), health (9%), travel (8%), restaurants/takeout (8%)
• Gender: men regular users 50% vs women 38%; women more likely to be non-users (38% vs 30%), but among users, women span more use cases
• Trust gap: 41% pay attention to AI search summaries; 29% say they trust them

The bottom line

AI now mediates discovery, comparison, and price confidence. If your brand isn't easy to parse, cite, and trust, you'll lose at the moment of choice. The fix is practical: structure the data, prove the claims, earn citations, and measure your presence where assistants do the deciding.