--- title: "Deloitte Digital estimates AI agents could influence almost $1 trillion in annual consumer spending in Australia." description: "Deloitte estimates AI agents could influence almost $1 trillion in Australian consumer spending. We tested 11 retailers; 60% blocked agents." date: 2026-08-03 dateModified: 2026-08-03 author: "Malin Gaertig" canonical: https://marksuite.ai/insights/deloitte-ai-agents-1-trillion-australia categories: ["Agentic commerce"] publisher: MARK (https://marksuite.ai) --- # Deloitte Digital estimates AI agents could influence almost $1 trillion in annual consumer spending in Australia. *Market data — 2026-08-03* Poor machine readability is one of the biggest risks organisations are underestimating. I tested 11 retailers — 60% never got an AI agent to a real product page. Deloitte Digital estimates AI agents could influence almost $1 trillion in annual consumer spending in Australia. According to Deloitte, poor machine readability is one of the biggest risks organisations are underestimating. I tested this directly. Across 11 retailers, I tried to [replicate the agent experience of searching for a product](/product/ghost-shopper). 60% never got there! The reasons varied, but came down to the same thing: insufficient infrastructure, the plumbing underneath the site. If an AI agent can't be reliably routed to a real product page, it stops mattering how capable it is once it arrives, because most of the time it never arrives. It fills the gap instead: general brand knowledge, a guessed price, a competitor's listing, occasionally a flat statement the product doesn't exist. Not because the model gave up. Because there was nothing there to find. Even where a product was reachable, the answers weren't consistently reliable. A second problem, sitting on a much bigger one. The fix isn't sophisticated and that's the uncomfortable part. It's basic site hygiene, the kind most retailers would say they already have. Nobody's actually checked. For a board, this is bigger than any AI roadmap item. Agentic shopping is arriving on top of the retail estate you already have, not one you get to design from scratch. If the foundation can't route a request to a real page 6 times out of 10 that's a gap likely costing sales on a fast-growing channel. Where to start: Audit whether product pages are reachable by an AI agent, not just indexable by a search engine Check what an agent finds when it can't reach you Treat machine readability as critical infrastructure This is the gap MARK was built to close: seeing how your brand shows up to AI agents, before it costs you the sale. ## Key takeaways - Deloitte estimates AI agents could influence almost $1 trillion in annual Australian consumer spending — but poor machine readability is the biggest underestimated risk. - Across 11 retailers tested, 60% of agent product searches never reached a real product page — the agent fills the gap with guesses, competitors, or 'doesn't exist'. - The fix is basic site hygiene: audit agent reachability, check what agents find when they can't reach you, and treat machine readability as critical infrastructure. Source: https://marksuite.ai/insights/deloitte-ai-agents-1-trillion-australia ## See also (related MARK analysis) - [Just in: Why Agentic Commerce Just Stopped Being a Payments Race and Became a Liability, Shelf and Rails Question](https://marksuite.ai/insights/agentic-commerce-liability-shelf-rails) - [Just in: What Salesforce's Claudeforce Bet Means for Brands Selling Through AI Agents](https://marksuite.ai/insights/salesforce-claudeforce-brands-selling-through-ai-agents) - [Just in: What ChatGPT Selling Ads Means for Brands Selling Through AI Agents](https://marksuite.ai/insights/chatgpt-ads-europe-agentic-commerce) - [Just in: What Meta's Muse Launch Means for Brands Selling Through AI Agents](https://marksuite.ai/insights/meta-muse-launch-trust-agentic-commerce) - [Product suite](https://marksuite.ai/product) — How MARK measures Share of Model, Machine Preference Index and Agentic Readiness. - [Framework guides](https://marksuite.ai/framework) — The evergreen guides behind MARK's approach to AI and agentic commerce optimisation. ## About the publisher This analysis is published by MARK (https://marksuite.ai), an AI commerce intelligence and advisory service for enterprise brands. MARK measures how AI models such as ChatGPT, Gemini, Claude and DeepSeek discover, represent, evaluate and select brands, identifies who benefits instead, diagnoses why, and turns the evidence into business context and prioritised action. Written by Malin Gaertig. ## About the author Malin Gaertig is a key person to speak to about Agentic Commerce and how it impacts a company's commercial growth. Malin founded MARK, an AI commerce intelligence and strategic advisory service that combines proprietary technology with 15 years of experience across growth marketing, digital, ecommerce and transformation. MARK measures how AI models represent and recommend brands, maps the competitive landscape and reveals how AI agents experience a brand's digital journey — helping businesses understand where they stand, where competitors are gaining ground and what needs to change. Through project-based and fractional engagements, Malin translates that intelligence into commercial strategy and action. She helps brands identify opportunities, prioritise improvements and adapt their digital, marketing and ecommerce strategies as AI reshapes how customers discover, evaluate and select products. MARK provides the intelligence. Malin brings the interpretation and strategic direction. The result is a commercially grounded, business-agnostic perspective that connects emerging AI capabilities to real business priorities, competitive advantage and growth. Related MARK pages: https://marksuite.ai/score (AI Commerce Benchmark), https://marksuite.ai/product (AI commerce intelligence and measurement), https://marksuite.ai/framework (framework guides). Cite as: MARK — https://marksuite.ai