--- title: "McKinsey just published one of the clearest breakdowns yet of what's actually happening to advertising economics as AI takes over discovery and purchase decisions." description: "McKinsey breaks down how AI is reshaping advertising economics from discovery through transaction — and why execution alone won't hold value." date: 2026-07-17 dateModified: 2026-07-17 author: "Malin Gaertig" canonical: https://marksuite.ai/insights/mckinsey-ai-advertising-economics categories: ["Agentic commerce"] publisher: MARK (https://marksuite.ai) --- # McKinsey just published one of the clearest breakdowns yet of what's actually happening to advertising economics as AI takes over discovery and purchase decisions. *Market data — 2026-07-17* AI is reshaping advertising economics from discovery through transaction. McKinsey lays out four possible trajectories — and the common thread is that execution alone won't hold value anymore. McKinsey just published one of the clearest breakdowns yet of what's actually happening to advertising economics as AI takes over discovery and purchase decisions. A few things stood out to me: → Search is being consolidated into AI environments. Over 50% of Google searches now show an AI overview, and up to half of open-web search traffic could be at risk by 2030. → AI is already mediating the transaction, not just the discovery. Shopping agents are ranking, comparing and in some cases completing purchases — McKinsey estimates 10-35% of e-commerce transactions could soon be initiated or influenced by AI-native experiences. → Value is concentrating in platforms that bundle data, measurement and transactions in one place. That's squeezing the traditional intermediaries such as ad networks and exchanges who historically connected buyers and signals separately. → 42% of advertisers already flag reliance on 'black box optimisation' as a top risk. You lose visibility into where your money actually lands. The most useful part of the report isn't the trend-spotting though — it's the four possible trajectories it lays out for where this heads: → AI evolution: usage keeps growing but humans still make the final call and most budget stays in existing channels → Closed-web shift: discovery consolidates inside AI answers and brands compete for visibility inside the response itself → Autonomous delegation: agents research, recommend and transact on a person's behalf; influence shifts from what a consumer clicks to the model doing the choosing on their behalf → Curated ecosystem: premium publishers and retailers pool authenticated audiences behind shared measurement, as a hedge against consumer scepticism of AI-generated answers. McKinsey is careful not to call a winner and poses that different categories will likely land in different places on this spectrum at different speeds. But the direction of travel across all four is the same: execution alone won't hold value anymore and the players who win are the ones building something hard to copy. For brands, the practical translation is simple: [being surfaced, recommended and selected by AI systems](/product/share-of-model) is now a distinct discipline from traditional paid media. If your product data, structured feeds and citations aren't built for machine evaluation, you're invisible to a growing share of the funnel — no matter how good your creative is. That's the reason I built MARK: to show brands how they show up in AI models, who gets chosen over them and why. ## Key takeaways - AI is consolidating search, mediating transactions and concentrating value in bundled platforms — traditional ad intermediaries are being squeezed. - McKinsey's four trajectories all point the same way: execution alone won't hold value; the winners build something hard to copy. - Being surfaced, recommended and selected by AI is now a separate discipline from paid media — product data, feeds and citations must be machine-readable. Source: https://marksuite.ai/insights/mckinsey-ai-advertising-economics ## See also (related MARK analysis) - [Just in: What Google's Ad Tech Ruling Means for Brands Betting on Agentic Commerce](https://marksuite.ai/insights/google-ad-tech-ruling-brands-betting-agentic-commerce) - [What Australia's UCP Checkout Rollout Means for Brands Selling Through AI Agents](https://marksuite.ai/insights/australia-ucp-checkout-rollout-brands-selling-through-ai-agents) - [Just in: What Australia's Trust Gap in Agentic Commerce Means for Brands Selling Through AI Agents](https://marksuite.ai/insights/australia-trust-gap-agentic-commerce-brands-selling-through-ai-agents) - [Just in: What Google Killing Assistant for Gemini Means for Brands Selling Through AI Agents](https://marksuite.ai/insights/google-killing-assistant-gemini-brands-selling-through-ai-agents) - [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