Google has dropped a lot of new features in Q2 2026, with the biggest wave arriving at Google Marketing Live in May. For performance marketers, keeping up with these releases is not optional. The platform is shifting fast, and the teams that understand what is changing will have a real advantage over those playing catch-up.
To break it all down, our performance marketing team gathered for an internal knowledge share. Team members Nathan Murdock, Gustavo Brito, Michelle Howard-Ta, Laura Schiele, Jen Shaw, Olivia Wesel, and Ashley Ali, each analyzing the major releases from Google’s annual product event for advertisers and marketers.
What follows is a summary of what they covered, what we think matters most, and how we are approaching these Google Ads features with clients.
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Conversational Discovery Ads and Highlighter Response Ads |
Place ads inside AI-generated search experiences |
Search, PMAX, and AI Max advertisers |
Audit website content and ad messaging |
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Business Agent for Leads |
Uses website content to answer questions and capture leads |
Lead generation advertisers |
Test with lower-risk audience segments |
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AI Max for Search |
Expands Search reach with broad match and AI-generated ad text |
Accounts with strong search volume |
Strengthen tracking and negative keywords |
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AI Brief |
Lets advertisers guide AI with brand and audience inputs |
AI Max and PMAX teams |
Add brand controls before scaling |
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Total Campaign Budgets and Demand-Led Pacing |
Automate budget distribution based on demand |
Seasonal, e-commerce, and lead gen campaigns |
Revisit monthly budget planning |
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Journey-Aware Bidding |
Uses soft conversions in bidding strategy |
B2B and long-sales-cycle accounts |
Clean up conversion actions first |
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Asset Studio |
Generates ad creative assets with AI |
Teams with limited creative resources |
Test output quality before broad use |
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Demand Gen updates |
Improve video creation and attribution |
YouTube, prospecting, and Display advertisers |
Plan the Display-to-Demand Gen transition |
The biggest shift Nathan Murdock flagged is that Google is starting to generate ad experiences directly inside AI-powered search responses. That means your website content is becoming a bigger input into paid search performance. In order to show up in these formats, advertisers need to be utilizing Performance Max and AI Max.
Conversational Discovery Ads appear inside AI-generated responses to user queries, while Highlighter Response Ads show up as sponsored recommendations within AI-generated lists. Both formats pull heavily from website content and existing ads to build more contextual ad experiences.
The practical implication is significant: Google’s AI is sourcing ad messaging directly from your website. If your pages are thin, outdated, inconsistent, or misaligned with your paid messaging, that disconnect can show up in these new formats.
Nathan stressed that this is where SEO and paid search are starting to merge in a very real way. Content quality is transcending organic search to become a key paid media input.
These formats currently require either Performance Max, also known as PMAX, or AI Max for Search. PMAX is Google’s automated cross-channel campaign type, while AI Max for Search uses broad match, advertiser assets, and generative AI to expand and customize Search campaigns.
Gustavo Brito covered Business Agent for Leads, which Google is positioning as a frictionless lead capture tool powered by a company’s existing website content.
Business Agent for Leads is a chatbot-style experience that draws from product pages, FAQs, and site content to answer user questions in real time. It ties into AI Max and PMAX and is expected to roll out more broadly by the end of 2026.
Gustavo’s recommendation is clear: treat website accuracy as a prerequisite before testing it. Because the bot generates responses from your content, outdated or misleading information becomes a liability.
For early tests, he recommends:
AI hallucinations are a real risk here, so ongoing oversight (which we always recommend) is especially critical.
Michelle Howard-Ta and Laura Schiele shared their experience running AI Max for Search. The results were mostly positive, but not without caveats.
AI Max for Search expands on traditional keyword matching, using broad match and generative AI to expand reach and dynamically customize ad text based on your asset library. It can help capture additional demand, but it needs clean data and close management.
Michelle’s testing on one client showed a slight dip in conversion rate, but higher volume and better overall efficiency for broad audiences. Laura has seen consistent improvements in conversion efficiency across accounts, but only when proper conversion tracking is already in place.
AI Max appears best suited for accounts with:
Negative keywords are still non-negotiable. Michelle shared that increasing the frequency of negative keyword reviews has been one of the most effective ways to keep AI Max campaigns performing well.
Michelle Howard-Ta and Laura Schiele shared their experience running AI Max for Search. The results were mostly positive, but not without caveats.
AI Max for Search expands on traditional keyword matching, using broad match and generative AI to expand reach and dynamically customize ad text based on your asset library. It can help capture additional demand, but it needs clean data and close management.
Michelle’s testing on one client showed a slight dip in conversion rate, but higher volume and better overall efficiency for broad audiences. Laura has seen consistent improvements in conversion efficiency across accounts, but only when proper conversion tracking is already in place.
AI Max appears best suited for accounts with:
Negative keywords are still non-negotiable. Michelle shared that increasing the frequency of negative keyword reviews has been one of the most effective ways to keep AI Max campaigns performing well.
Jen Shaw previewed AI Brief, a feature that lets advertisers input brand guidelines to guide how Google’s AI generates ad messaging and targeting within AI Max and PMAX.
AI Brief gives advertisers a way to steer AI outputs with messaging guidelines, keyword matching preferences, and audience controls. Jen sees this as a meaningful step toward regaining control over automated campaign output.
The feature also supports iterative testing with real-time previews, which should help reduce off-brand messaging. Once it rolls out fully, it should become a standard part of any AI Max setup.
Google’s newer budget and bidding tools are designed to shift spend based on demand, not just fixed daily limits.
Total Campaign Budgets allow Google to distribute spend dynamically across days without exceeding the campaign’s overall budget. Jen explained that this can reduce the manual budget management that causes campaigns to miss high-intent moments when daily caps are hit too early.
Olivia Wesel highlighted its value for seasonal demand spikes, including back-to-school and Black Friday windows. The rollout is expected in the coming months, so teams should start thinking through how it affects monthly planning.
Demand-Led Pacing adjusts spend upward during high-demand periods and pulls back during slower periods. The initial focus is shopping and e-commerce, but the same logic applies to lead generation.
Olivia suggested it could help smooth out the lead quality drops that often happen around holidays by automatically adjusting where spend goes.
Reliable conversion tracking is the foundation for any of this to work. Without strong signals, the AI has nothing useful to learn from. Although this isn’t a certainty, the team collectively noted the potential for Google to chew through budget quickly if its algorithm recognizes “higher demand,” which wouldn’t guarantee any pipeline impact.
In short, guardrails and frequent checks, particularly in the first stage post-release, are critical to ensure your spend isn’t burned up unexpectedly.
Journey-Aware Bidding is a beta feature that incorporates soft conversions, such as page views and newsletter signups, into bidding strategies. Instead of optimizing only toward last-click conversions, it considers earlier signals in the customer journey.
Jen and Olivia see this as especially useful for B2B clients, where sales cycles are long and conversion paths rarely move in a straight line.
The main requirement is conversion hygiene. Too many irrelevant signals will dilute the algorithm’s ability to optimize effectively.
Asset Studio is Google’s AI-driven tool for generating headlines, descriptions, and other creative elements. It is expected to become fully available over the summer and gain video generation capabilities.
Olivia sees clear value for accounts without dedicated creative teams or for advertisers that want to run rapid creative tests without a design bottleneck.
The main concern is B2B tech. The tool tends to generate real-life lifestyle imagery, while many B2B tech brands perform better with more abstract or technology-focused visuals. It is worth testing, but the output needs close review.
Ashley Ali walked through the updates coming to Demand Gen, Google’s campaign type for visual, video, and discovery-style demand generation.
New multi-modal video creation tools can produce a library of YouTube ads from answers to a simple set of questions. That should make it easier to scale video creative for prospecting campaigns.
Attribution is also improving. New tracking links brand search activity back to users who were exposed to Demand Gen ads, giving teams a cleaner view of how these campaigns contribute to pipeline beyond direct clicks. A View-Through Conversion bidding beta is also available, helping optimize for conversions that happen after an ad view rather than only after a click.
The most operationally significant announcement: Google Display campaigns are being phased out. By January 2027, display inventory is expected to be exclusive to Demand Gen campaigns. If clients are still running standalone Display, now is the time to plan the transition.
Across the knowledge share, a few consistent recommendations emerged.
First, fix conversion tracking before turning on more automation. AI Max, journey-aware bidding, demand-led pacing, and PMAX all depend on reliable signals.
Second, align website content with ad messaging. As Google pulls more from your site to build ad experiences, content accuracy directly affects paid media performance.
Third, start with controlled tests. Use lower-risk segments, monitor performance closely, and expand only when the data supports it.
Fourth, keep negative keyword management active. Broad match and AI expansion can drive efficiency, but only with guardrails.
Finally, prepare for Demand Gen now. If Display is still part of your media mix, start planning migration, creative, targeting, and measurement before the January transition.
Google is building a version of paid search where AI generates the ad experience, sources messaging from your website, manages budget pacing, adjusts bids across the customer journey, and creates creative assets.
The marketer’s job is increasingly about strategy, oversight, and input quality. The teams that build clean conversion tracking, aligned website content, and rigorous testing processes will be better positioned as these tools mature.
Want to talk through how these changes affect your account specifically? Reach out to our team for an AI Max readiness review, conversion tracking audit, Demand Gen transition plan, or website/ad messaging alignment check.
AI Max for Search is a Google Ads capability that uses broad match, advertiser assets, and generative AI to expand Search reach and customize ad text. It can improve volume and efficiency, but it works best when conversion tracking is reliable and negative keywords are actively managed.
Advertisers should first audit conversion tracking, website accuracy, and ad-message alignment. Google’s AI tools rely heavily on these inputs, so weak tracking or outdated website content can lead to poor optimization, low-quality leads, or inaccurate messaging.
Standalone Google Display campaigns are being phased out, with display inventory expected to move into Demand Gen by January 2027. Advertisers still running Display should begin planning their Demand Gen transition, including creative, attribution, bidding, and audience strategy.