Google has rolled out three AI-powered advertising tools designed to reduce manual campaign management and improve conversion efficiency for merchants running Search and Shopping campaigns, the company announced ahead of its Marketing Live event in May 2026.
The updates include journey-aware bidding in beta for Search Ads, expanded Smart Bidding Exploration across Performance Max and Shopping, and demand-led budget pacing that adjusts daily spend based on consumer behavior patterns. The tools build on Google’s push to automate more campaign optimization through machine learning, a strategy that has driven mixed reactions from advertisers who value control alongside efficiency.
Journey-Aware Bidding Tracks Non-Biddable Conversions
The most significant new feature is journey-aware bidding, now in beta for Google Search Ads. The tool allows Google’s AI to learn from both biddable conversion goals (such as purchases) and non-biddable events (such as newsletter signups, content downloads, or product page visits) across the full customer journey from initial lead contact through final sale.
This marks a shift in how Google’s automated bidding uses conversion data. Previously, Smart Bidding optimized primarily toward actions advertisers were willing to pay for directly. Journey-aware bidding instead uses the full spectrum of user behavior to predict purchase intent and adjust bids accordingly, even when intermediate steps are not assigned bid values.
For merchants with longer sales cycles or multi-touch customer journeys, this could improve bid accuracy by incorporating signals that previously sat outside the optimization loop. A furniture retailer, for example, might see better results if Google’s system learns that users who request a catalog or use a room visualizer tool convert at higher rates, even if those actions themselves are not assigned a cost-per-action bid.
The limitation is that journey-aware bidding requires advertisers to track and pass multiple conversion events to Google Ads, which means implementation depends on proper event tagging and data integration. Merchants without robust analytics setups may struggle to take advantage of the feature.
Smart Bidding Exploration Expands to Performance Max
Google is also extending Smart Bidding Exploration, a feature that tests bid variations to discover new converting audiences, beyond Search campaigns. According to the company, Search campaigns using the feature have seen an average 27% increase in unique converting users.
The tool is now entering beta for Performance Max campaigns, with a separate beta for Performance Max with product feeds and Shopping campaigns launching in the coming weeks. Performance Max, which runs ads across Google’s full inventory including Search, YouTube, Display, and Gmail, has become a core channel for ecommerce advertisers since its full rollout in 2022, but it has also drawn criticism for limited transparency and control.
Expanding exploration-based bidding to Performance Max could help merchants reach incremental customers, but it also increases reliance on Google’s black-box optimization. Advertisers will need to monitor whether exploration drives genuinely new customers or simply shifts budget toward lower-intent placements with weaker return on ad spend.
Demand-Led Pacing Adjusts Daily Budgets Automatically
The third update, demand-led pacing, automates daily budget allocation within Search and Shopping campaigns. Instead of spending evenly across a billing period, Google’s system will now increase spend on high-demand days and reduce it when consumer interest is lower.
This could benefit merchants with fluctuating demand patterns, such as seasonal sellers or brands sensitive to weather, events, or trending topics. A swimwear brand, for instance, might see Google automatically increase spend on warm weekends in May and pull back on rainy weekdays, rather than forcing the advertiser to manually adjust budgets throughout the month.
Demand-led pacing builds on campaign total budgets, a feature Google launched earlier in 2026 that replaced daily budgets with monthly or custom-period caps. According to Google, advertisers using total budgets reduced manual budget adjustments by an average of 66% compared to daily budget management.
The risk is that demand-led pacing could front-load spend early in a budget period if Google’s AI misreads demand signals, leaving campaigns underfunded later in the month. Merchants should monitor pacing closely in the first few cycles and ensure monthly budget caps are set conservatively to avoid overspend.
Keep an Eye on the Following
These updates reinforce Google’s broader strategy of shifting campaign control from advertisers to automated systems. For merchants, the trade-off is clear: less day-to-day management in exchange for less granular control over where budgets go and how bids are set.
Merchants running Search or Shopping campaigns should evaluate whether journey-aware bidding aligns with their conversion tracking setup. Those already passing multiple event types to Google Ads may benefit from joining the beta. Merchants with limited event tracking should prioritize instrumentation before adopting journey-aware optimization.
For Performance Max users, the arrival of Smart Bidding Exploration introduces another layer of automated testing. Advertisers should establish clear benchmarks for cost per acquisition and return on ad spend before enabling exploration, and compare performance across test and control groups where possible.
Demand-led pacing requires less active decision-making from merchants, but it also demands closer monitoring of spend curves throughout the budget period. Advertisers accustomed to stable daily pacing may need to adjust internal forecasting and reporting to account for more variable daily costs.
Outlook
Google is expected to detail additional AI advertising features at Marketing Live later in May 2026. The company has steadily reduced manual controls in Google Ads over the past three years, pushing merchants toward automated bidding, broad match keywords, and AI-generated creative assets.
The success of these tools will depend on whether Google’s optimization models can consistently outperform human-managed campaigns across diverse product categories, margins, and customer lifecycles. Early performance data from journey-aware bidding and demand-led pacing will be critical for merchants deciding how much control to cede to Google’s algorithms.
