Ahead of Times – Issue #9

Google’s Universal Cart: search becomes checkout 

Google is pushing further into owning the purchase journey, with AI bringing discovery, comparison and checkout into a single experience. Shopping no longer needs to happen across multiple sites, it can take place directly inside Search and Gemini, where users can add products to a shared cart and, in some cases, complete the purchase without leaving Google. 

At the centre of this is Universal Cart. Rather than managing separate baskets across different retailers, users now have one unified cart that follows them across Search, YouTube, Gmail and Gemini. Products from multiple retailers can be added into the same basket, while AI works in the background to compare options, track price changes, highlight stock availability and even flag potential compatibility issues. 

When it comes to completing the purchase, the process becomes just as seamless. Users can check out in a few taps using Google Pay or choose to pass through to the retailer at the final step if needed. 

As Ben Ladbrook, our Performance Lead at S&T, puts it: “Google is no longer just a search engine sending traffic to your site; they want to become a transaction engine.” 

It’s a small change in behaviour, but a big shift in control.  

Google’s new intelligent shopping basket is starting to roll out across Search and the Gemini app in the US this summer. 

Why this matters: 

For years, the job of paid search has been to get the click and send users to a site, where the landing page and checkout take over. That model is now changing. 

If users are checking out inside Google, your product feed becomes your shop window. Brands with clean, complete and well-structured product data will win. If your data’s bad, you won’t show up. 

There’s also a broader question around how far this should go. Jeff, our Head of Performance, touches on this in his blog on what it means for brands when Google starts to own more of the journey end to end. You can read his take here: Google’s Universal Cart: a step too far? 

The new way of search: Intelligent Search Box  

Queries in Search are getting longer and more natural, AI Mode has passed one billion monthly users, and Google reported that total search queries reached an all-time high last quarter. At the same time, people are clicking through to websites less often, as AI-generated answers resolve more of the journey directly within the results page. 

To support this, Google introduced its Intelligent Search Box, the biggest upgrade to Search in over 25 years. It expands to give users space to describe exactly what they need, with AI-powered suggestions that go beyond autocomplete and help shape the query. It also supports inputs across text, images, files, videos and Chrome tabs. It keeps context and allows follow-up questions, turning search into an ongoing interaction rather than a single query. 

Why it matters:

Search is moving away from keywords and towards conversations. 

For brands and publishers, this changes how visibility is earned. It is no longer enough to rank for a specific term. Content needs to cover broader questions and be structured in a way that AI can interpret and use when generating answers. 

Clicks are no longer guaranteed. AI Overviews and conversational results are resolving more queries without users leaving the page, reducing traffic even as intent remains strong. 

We’re already seeing how this is playing out in practice. Ads are now being embedded directly within AI answers, and platforms are shifting towards AI-first campaign and match types such as Performance Max and AI Max. 

For marketers, the shift is happening earlier in the journey. Influence is no longer just about driving traffic, but about being part of the consideration set the AI builds. The challenge is not just ranking higher but showing up when the AI selects what to surface, compare and recommend. 

TikTok: AI across the full advertising workflow 

TikTok also had its annual product summit in May, where AI was clearly embedded across the entire advertising workflow, from creator discovery and creative production through to campaign execution and measurement.  

The updates span multiple areas. On the creative side, TikTok is expanding its Symphony suite with new AI video capabilities, including Dreamina Seedance 2.0, designed to produce consistent, high-quality content at scale without the level of manual fixes that traditionally slow production.  

On the performance side, its Smart+ solution continues to evolve towards fully automated campaign management, with features that centralise assets, select the best-performing creative and surface optimisation recommendations. 

Alongside this, TikTok introduced its Model Context Protocol (MCP) server, joining Google and Meta in opening up its ad platform to AI-driven workflows, and moving towards a more agentic approach to media buying. 

Why this matters:

 AI is increasingly being used to automate parts of the advertising workflow, from creative production through to campaign optimisation. The direction is consistent across Google, Meta and TikTok, with more reliance on AI to interpret signals, optimise performance and drive outcomes. 

The change is not just about doing things faster. It is about how work is structured. Campaigns are becoming more connected, with less separation between insight, creative and execution. 

More value is now tied to inputs, signals and decision-making, rather than manual campaign build and optimisation 

From DSA to AI Max for Shopping 

Google has confirmed it’s officially sunsetting Dynamic Search Ads (DSA) this September, replacing them with AI Max. The bigger news for ecommerce is AI Max for Shopping, a single toggle on standard Shopping campaigns that uses Gemini to understand the meaning behind a search, rather than matching on product feed text. Alongside this, Smart Bidding has been upgraded to ‘Journey-Aware Bidding’, which optimises across the whole multi-step path to purchase rather than just the last click. 

Why this matters: 

This follows the same direction as Performance Max but applied to Shopping. Less manual control, more machine learning, and a stronger reliance on broader, conversational intent. 

In this environment, performance is driven by signal quality. Clean conversion tracking, strong product data and consistent inputs are what the platform uses to decide what to show and how to optimise. 

That puts more weight on the data foundation. Server-side tracking, enhanced conversions and solutions like Google Tag Gateway directly influence how well platforms can interpret signals and make decisions. 

Advertisers with stronger data and clearer inputs are better placed to benefit as these systems take on more of the optimisation 

AI gets physical: Google follows Meta into smart glasses 

Google is pushing further into wearable AI with the next phase of Android XR: intelligent eyewear. 

The roadmap includes two types of devices. Audio glasses, which provide spoken assistance in real time, and display glasses, which surface information directly in front of the user when it’s needed. The first audio versions, built with partners like Samsung, Gentle Monster and Warby Parker, are expected to arrive first, with display-based devices likely to follow. 

This puts Google on a similar path to Meta, which already has AI-enabled glasses in market. Instead of pulling out a phone or opening a browser, users can access context, answers and prompts in real time, layered over what they are seeing. 

This is AI moving from something we use, to something that sits alongside us, embedded into everyday moments. 

Why this matters:  

This opens a new front for how people interact with content, and how they might be reached. 

If information is surfaced through wearable devices, discovery shifts from screens into real-world moments. As the technology evolves, this is likely to become another channel for advertising, shaped by what people see, where they are and what they engage with. In practice, that could mean nearby reviews, offers as someone walks past a store, or suggesting products based on what they are looking at in real time. 

At the same time, it raises bigger questions around privacy. Devices that continuously capture visual, audio and behavioural signals bring a level of data collection much closer to the user, with more reliance on personal context to shape what is shown.