Google AI Max for Search: Complete Setup Guide 2025

When Google announced AI Max for Search at Google Marketing Live in May 2025, the promises were extraordinary: 14% average conversion lift, with up to 27% for campaigns using exact and phrase match keywords. Case studies showcased conversion surges of 263% and cost-per-acquisition reductions of 73%. But here's what Google didn't lead with: independent testing by Monks Agency found that 99% of AI Max impressions generated zero conversions across approximately 30,000 search terms, and a LinkedIn poll of PPC professionals revealed only 16% reporting good performance with the feature.

This isn't a story of Google making false promises or AI Max being worthless. It's a story about the massive gap between cherry-picked success stories and typical advertiser experiences. At Digital Applied, we don't tell you what Google wants us to say—we tell you what actually works. This guide presents both Google's official claims and independent testing results so you can make informed decisions about whether AI Max belongs in your advertising strategy.

AI Max for Search is a suite of AI-powered enhancements for Google Search campaigns that uses keywordless matching, generative ad copy, and dynamic landing page selection to expand your campaign reach beyond traditional keywords. When it works, it discovers high-converting queries you'd never think to target manually. When it doesn't, it burns budget on irrelevant clicks while providing limited transparency into why. Success depends heavily on your industry vertical, campaign structure, budget size, and willingness to actively manage an AI system that requires human oversight.

What is Google AI Max for Search?

AI Max for Search is not a new campaign type—it's an optional suite of AI-powered enhancements that can be enabled within new or existing Google Search campaigns. Officially announced on May 6, 2025 via the Google Ads blog and featured prominently at Google Marketing Live on May 21, 2025, AI Max began its global rollout in Q3 2025. It's currently available in the Google Ads web interface, Google Ads Editor, and Search Ads 360, with full API support arriving in H2 2025.

The core premise is straightforward: AI Max applies Google's latest artificial intelligence technology to three key campaign elements—search term targeting, ad copy creation, and landing page selection—to find conversions your traditional keyword-based campaigns miss. Unlike Performance Max, which operates as a black box across all Google properties, AI Max maintains the transparency and control of Search campaigns while adding AI-powered expansion capabilities on top of your existing keyword structure.

Each feature can be toggled on or off independently at the campaign or ad group level, giving you granular control over how aggressively AI Max expands your campaigns. You can start conservatively with just search term matching, or enable all three features together for maximum AI-powered expansion. Google's case studies highlighting 263% conversion surges typically involve advertisers enabling all three features simultaneously, while more cautious implementations using selective feature activation report more modest (and more typical) results.

AI Max requires Smart Bidding strategies focused on conversions (Max Conversions or Max Conversion Value with optional CPA/ROAS targets), a minimum of 30 conversions in the past 30 days, and at least $50 daily budget. However, agency testing suggests the recommended budget is actually 15 times your target CPA—meaning if your target cost-per-acquisition is $50, you should budget $750 per day for optimal AI Max performance. This significant budget requirement is one reason why AI Max isn't suitable for all advertisers, despite Google's broad rollout.

AI Max vs Performance Max: Complete Comparison

The most common misconception about AI Max is that it replaces Performance Max. It doesn't. These are complementary tools serving different strategic purposes, and Google explicitly recommends using both together in what they call the "Power Pack" approach. AI Max enhances Search campaigns specifically, while Performance Max operates as a standalone multichannel campaign type across all Google inventory. Understanding when to use each—or both—is critical for effective Google Ads strategy.

The Portfolio Approach (Recommended)

Rather than choosing one or the other, Digital Applied recommends a portfolio strategy for most advertisers: allocate 40-50% of budget to traditional Search campaigns for core brand and high-intent terms, 25-30% to AI Max Search for expansion and discovery, and 20-25% to Performance Max for multichannel reach and remarketing. This approach captures the benefits of each campaign type while hedging against the weaknesses of any single automated solution. Your traditional Search campaigns provide the stable baseline performance, AI Max discovers new Search opportunities with transparency, and Performance Max extends your reach beyond Search into visual and video channels where intent-based targeting excels.

Key Features & Capabilities

AI Max for Search consists of three main features that work independently or together to expand your campaign reach beyond traditional keyword targeting. Each feature addresses a specific limitation of manual Search campaigns, and each comes with its own set of benefits and risks that require careful management.

Campaign-Level Negative Keywords

One of AI Max's most significant advantages over Performance Max is full support for negative keywords at both campaign and ad group levels. This gives you the ability to proactively block irrelevant search terms, competitor brands, and low-quality queries before they waste budget. Comprehensive negative keyword lists before launch are essential—don't expect AI to understand what you don't want to target. Set exclusions first, then let AI explore within those boundaries.

Smart Bidding Exploration (Related Feature)

Announced alongside AI Max at Google Marketing Live 2025, Smart Bidding Exploration represents Google's biggest bidding update in over a decade. It expands Smart Bidding to explore high-potential search queries previously overlooked, including more general or early-stage customer intent queries. While AI Max handles targeting and creative expansion, Smart Bidding Exploration handles bid optimization for newly discovered opportunities. Google claims it delivers an 18% increase in unique search query categories with conversions and 19% more conversions on average, but requires Target ROAS bidding with 10-30% ROAS flexibility. The two features work together but can be used independently.

Complete Setup Guide: Step-by-Step

Setting up AI Max correctly from the start significantly impacts your results. The difference between successful implementations and failed tests often comes down to proper prerequisites, strategic feature selection, and choosing the right testing methodology. Here's how to set up AI Max for the best chance of success.

Prerequisites Checklist

Setup Option 1: New AI Max Campaign

1. Create New Campaign: In Google Ads, click "+" → "New campaign" → Select "Search" as campaign type → Choose conversion goals
2. Configure Bidding: Select Max Conversions or Max Conversion Value → Optionally set target CPA or ROAS → Set daily budget (minimum $50, recommended 15x CPA)
3. AI Max Opt-In: When you reach the "AI Max" page during creation, toggle to opt-in → All three features enabled by default
4. Configure Features: Choose which features to enable (conservative: search term matching only; aggressive: all three)
5. Set Exclusions: Add brand exclusions, URL exclusions, and campaign-level negative keywords
6. Complete Setup: Add keywords (will work alongside AI), create RSA ads, configure targeting
7. Ad Group Settings: Toggle search term matching per ad group, add URL inclusions, set locations of interest if needed

Setup Option 2: Enable on Existing Campaign

1. Verify Eligibility: Confirm campaign uses Smart Bidding and meets minimum requirements
2. Access AI Max Settings: Within campaign settings, locate "AI Max" section → Toggle to enable
3. Configure Campaign-Level: Choose features to enable → Set URL exclusions and brand settings
4. Configure Ad Group-Level: Toggle search term matching per ad group → Add URL inclusions
5. Monitor Closely: Watch for performance changes during 2-4 week learning period

Setup Option 3: Test with Experiments (Recommended)

This is the safest approach for testing AI Max without risking your existing campaign performance. Digital Applied recommends this method for all first-time AI Max implementations.

1. Create Experiment: Navigate to "Experiments" in Google Ads → Select campaign to test → Choose "Create custom experiment"
2. Set Parameters: Base Campaign = existing Search (control) → Experiment Campaign = duplicate with AI Max (treatment) → 50/50 traffic split
3. Enable AI Max: In experiment campaign only, enable AI Max settings → Choose features to test
4. Match Budgets: Apply same daily budget to both campaigns for fair comparison
5. Run 4+ Weeks: Minimum 2-4 weeks learning period plus 2+ weeks evaluation period
6. Evaluate Results: Compare conversions, CPA/ROAS, conversion rate, search terms quality
7. Decision Point: If experiment wins, apply AI Max to base campaign → If underperforms, disable and optimize approach

Feature Selection Strategy

Conservative Approach: Start with search term matching only, monitor for 2-4 weeks, then add text customization if performing well, finally add final URL expansion only if website is comprehensive and well-organized. This staged rollout minimizes risk and isolates which features drive results.

Aggressive Approach: Enable all three features together from day one for maximum AI-powered expansion. This is what Google's highest-performing case studies did (L'Oréal, Royal Canin, ClickUp), but it also carries the highest risk of budget waste if relevance issues occur. Only recommended for well-optimized accounts with adequate budgets and comprehensive websites.

Selective Approach: Enable different features at different ad group levels based on performance and risk tolerance. For example, enable all features for non-brand generic ad groups, but only search term matching for product-specific ad groups, and disable AI Max entirely for brand defense ad groups.

Performance: Google's Claims vs Independent Testing

This is where we separate marketing promises from actual results. Google's official announcement promised extraordinary performance gains, backed by cherry-picked case studies. Independent testing tells a dramatically different story. Both data sets are real—they just represent opposite ends of the performance spectrum.

Google's Official Claims (May 2025)

Google's Featured Case Studies

These case studies represent Google's most successful implementations—not typical results. Selection bias in case studies is standard marketing practice, but creates unrealistic expectations for average advertisers.

Independent Testing Results

Why the Reality Gap Exists

The massive discrepancy between Google's 14-27% improvement claims and the community's 84% neutral/negative results isn't about false advertising—it's about selection bias and context dependency. Here's what creates the gap:

1. Cherry-Picked Case Studies: Google features only their most successful implementations. Royal Canin's 263% surge and Klook's 161% increase are real, but they represent the top 1% of outcomes, not typical performance.
2. Industry Vertical Matters Enormously: The fact that Google explicitly excludes retail from the 14% benchmark is a massive red flag for ecommerce advertisers. E-commerce success stories like Royal Canin suggest retail CAN work, but the exclusion implies it often doesn't.
3. Account Maturity Affects Results: Well-optimized accounts with 5+ years of performance data see fewer gains because AI Max has fewer opportunities to add value. Newer accounts or those heavily reliant on exact match benefit more because there's more untapped search volume to discover.
4. Implementation Quality Varies Widely: ClickUp's success came from enabling all three AI Max features together. Partial implementations or those without proper negative keywords see worse results.
5. Budget Adequacy is Critical: Real-world testing shows $750/day budgets (15x target CPA) deliver significantly better results than the $50/day minimum. One home services company saw 8 conversions weekly at $100/day plateau at 47 conversions weekly when budget increased to $750/day—same $50 CPA but 6X more volume.
6. Beta Participants vs. General Rollout: Google's 14% data comes from beta participants who were likely highly engaged, well-optimized advertisers actively working with Google representatives. General rollout participants testing independently see very different results.

The Critical Retail Exclusion

Google's decision to explicitly exclude retail advertisers from the 14% conversion lift benchmark deserves scrutiny. This exclusion appears in the official May 2025 blog announcement and is reinforced in support documentation. The implication is that retail/ecommerce advertisers either (a) don't see the 14% lift, or (b) performance is so variable that including retail would significantly lower the reported average. Yet paradoxically, Google's most impressive case studies feature ecommerce brands like Royal Canin (263% surge) and L'Oréal (2X conversion rate). This suggests retail CAN succeed with AI Max, but it's far from guaranteed—hence the exclusion from the general benchmark to avoid accountability when results disappoint.

Expert Consensus

Industry experts have reached consensus on AI Max performance: "Early results show positive, neutral, or negative outcomes, with neutral to negative outcomes being more common—especially in accounts with strong existing setups, where AI Max has fewer opportunities to add value." This isn't a failure of AI Max as a technology—it's a reality check on Google's marketing. AI Max works exceptionally well for specific scenarios (exact/phrase-heavy campaigns, adequate budgets, comprehensive websites, industries with conversational search patterns), but it's not the universal 14-27% lift solution Google's announcement implied. Setting realistic expectations matters: achieving 10% improvement with AI Max is a success, not a disappointment—you're outperforming 84% of advertisers who report neutral or negative results.

Success Factors & Best Practices

After analyzing Google's case studies, independent testing, and agency implementations, clear patterns emerge around what makes AI Max succeed. These aren't guarantees—remember that 84% of advertisers report neutral or negative results—but they significantly improve your odds of being in the successful 16%.

Campaign Prerequisites

• Smart Bidding Already Working: AI Max amplifies Smart Bidding performance. If your Target CPA or Target ROAS isn't stable and delivering results, fix that before adding AI Max complexity.
• Quality Conversion Tracking: 30+ conversions minimum, but 100+ monthly conversions deliver optimal performance from day one. Enhanced Conversions and Data-Driven Attribution should be active.
• Comprehensive Negative Keywords: Don't expect AI to understand what you don't want. Build extensive negative keyword lists before enabling AI Max, including competitor brands, low-intent queries, and irrelevant variations.
• Budget Adequacy: The $50/day minimum is technically required, but agency testing shows $750/day (15x target CPA) is what actually delivers consistent results. One home services company plateaued at 8 conversions weekly with $100/day but reached 47 weekly conversions at $750/day—same CPA, 6X more volume.

Account Structure That Excels

Exact and Phrase Match Heavy Campaigns: This is where Google's 27% lift claim applies (versus 14% average). Campaigns that rely heavily on exact and phrase match have the most untapped search volume for AI Max to discover. If you're already using 70%+ broad match, AI Max likely won't help—you're already capturing the expansion it would provide.

Maxed Out Impression Share: Campaigns already showing for 90%+ of searches on current keywords can't grow without expanding targeting. AI Max finds the incremental volume traditional keywords miss, making it ideal for accounts that have fully optimized existing keyword strategies.

Website Content Quality

AI Max needs comprehensive, well-organized landing pages to function properly. Text customization pulls headlines from your site content—if product descriptions are thin or blog content is sparse, the AI has less material to work with. Final URL expansion requires multiple relevant landing pages for different offerings. One advertiser noted that "blog articles are converting at a significantly higher ROAS" with AI Max, suggesting rich educational content can outperform product pages for certain queries.

Warning: As one expert cautioned, "If your website isn't a strong representation of your company, AI Max for Search might not be a great idea if you leave the Text Customization and Final URL expansion on." Poor website quality limits AI Max's effectiveness and increases the risk of sending traffic to wrong pages.

Best-Performing Industries

Active Management Requirements

AI Max is not "set and forget." Successful implementations require daily monitoring during the first 2 weeks, then weekly search terms review ongoing. Watch for competitor brand bidding (AI Max targets high proportions of competitor terms), search term relevance issues (queries "completely missing user intent"), and Search Partner Network problems (37% lower ROAS on SPN according to Intelligency Group). Many experts recommend excluding Search Partner Network entirely when using AI Max due to "deeply disturbing" expansionary patterns. Add negative keywords promptly, review RSA headline performance, and be prepared to pause campaigns that burn budget without delivering conversions.

When to Use AI Max (and When to Avoid)

AI Max isn't suitable for everyone. Based on performance data from both successful implementations and failed tests, here's when to test AI Max and when to wait.

Test AI Max If You Have:

Avoid AI Max If You Have:

Decision Framework

Ask yourself: (1) Do I have exact/phrase match-heavy campaigns with room to expand? (2) Can I allocate $750+/day for testing? (3) Do I have 100+ monthly conversions and quality tracking? (4) Is my website comprehensive and well-organized? (5) Am I willing to actively monitor and optimize for 4+ weeks? If you answer yes to all five, test AI Max with experiments. If you answer no to three or more, wait until your account meets more prerequisites. The 16% success rate means most advertisers don't see good results—stack the odds in your favor before testing.

Optimization Strategies for Better Results

AI Max requires active optimization to succeed. Unlike traditional Search campaigns where you optimize keywords and bids, AI Max optimization focuses on guiding the AI's exploration through strategic exclusions and signal reinforcement.

First 2 Weeks: Daily Monitoring

Search Terms Review (Daily): Download the search terms report filtered to "AI Max" match type. Look for three red flags: (1) Competitor brand terms consuming budget, (2) Queries that completely miss user intent, and (3) High-impression, zero-conversion terms (the Monks Agency pattern). Add negative keywords immediately—don't wait for statistical significance.

RSA Headline Analysis: The search terms report shows which headlines served with each query. Identify headlines generating conversions versus those burning budget. While you can't remove AI-generated headlines directly, you can disable text customization if generic AI copy outperforms your manual assets (or vice versa).

Landing Page Performance: If using Final URL expansion, check which pages AI is selecting. Look for patterns like "AI keeps sending traffic to blog posts instead of product pages" or "About page getting Search traffic." Add URL exclusions for pages that shouldn't receive paid traffic, and URL inclusions at ad group level for pages that should be prioritized.

Weeks 3-4: Learning Period Evaluation

Performance Comparison: If running experiments, compare control vs treatment after 2-4 weeks. Look beyond aggregate metrics—segment by match type to see if AI Max traffic performs differently than traditional keyword traffic. Check conversion rates, not just conversion volume (AI Max can deliver more conversions at worse efficiency).

Budget Pacing: Is the campaign spending its full budget? Budget-limited campaigns prevent AI from exploring new opportunities. Consider increasing budget if seeing positive signals, or decreasing if burning through spend without conversions.

Search Partner Network Audit: Segment performance by network (Google Search vs Search Partners). If Search Partner Network shows 30%+ lower ROAS (common pattern), exclude SPN from the campaign. Many experts recommend this by default given AI Max's "deeply disturbing" expansionary patterns on SPN.

Ongoing Optimization (Weekly)

Negative Keyword Expansion: AI Max requires more aggressive negative keyword management than traditional Search. Build negative lists around competitor brands, low-intent queries, informational searches that don't convert, and any search patterns burning budget. Unlike Performance Max, AI Max respects both campaign and ad group level negatives—use this advantage.

Extract High Performers: Identify search terms from AI Max that consistently convert well, then add them as exact match keywords to your traditional Search campaigns. This "harvests" AI Max discoveries while maintaining control over bidding and messaging for proven queries.

Feature Toggle Testing: If all three features are enabled and performance is mixed, try disabling features one at a time to isolate what works. Start by disabling Final URL expansion (highest risk of wrong pages), monitor for a week, then re-enable or keep disabled based on results. Repeat with text customization and search term matching until you find the optimal combination for your account.

When to Pause AI Max

Advanced: Portfolio Rebalancing

If AI Max performs well in testing, gradually shift budget from traditional Search to AI Max—but maintain both. Digital Applied recommends 40-50% traditional Search (core terms), 25-30% AI Max (expansion), 20-25% Performance Max (multichannel). Monitor overall account ROAS, not just campaign-level metrics, to ensure AI Max delivers true incrementality rather than stealing conversions from other campaigns. If overall ROAS declines as AI Max budget increases, you have a cannibalization problem, not a growth opportunity.

Conclusion: Setting Realistic Expectations

AI Max for Search represents Google's vision of AI-powered advertising's future—campaigns that discover opportunities you'd never find manually, generate contextually relevant ad copy in real-time, and dynamically match users to your best landing pages. When it works, it's genuinely impressive: Royal Canin's 263% conversion surge, ClickUp's 20% lift with higher ROAS, Klook's 161% conversion value increase. These outcomes are real, documented, and achievable.

But they're not typical. The reality gap between Google's 14-27% improvement promises and the community's experience—where 84% report neutral or negative results and one major agency found 99% of impressions with zero conversions—isn't about Google lying. It's about the massive variability in outcomes based on industry vertical, account maturity, budget adequacy, website quality, and implementation approach. AI Max works exceptionally well for exact/phrase match-heavy campaigns with $750+/day budgets, comprehensive websites, and advertisers willing to actively manage keywordless expansion. It struggles with lead generation without offline tracking, regulated industries requiring message control, budget-constrained small businesses, and accounts already heavily using broad match.

At Digital Applied, we don't tell clients what Google wants us to say—we tell you what actually works based on both official data and independent testing. Our recommendation for AI Max: Test it if you meet the success criteria (exact/phrase-heavy, adequate budget, quality tracking, comprehensive website), but use experiments rather than wholesale adoption. Give it 4+ weeks to learn and optimize, but don't hesitate to pause if it's burning budget without delivering conversions. Achieving 10% improvement is a success that puts you ahead of 84% of advertisers—don't measure yourself against Google's cherry-picked 263% case study.

The most important insight from six months of AI Max testing: It's a complementary tool, not a replacement for traditional Search campaign management. The advertisers seeing the best results run a portfolio approach—40-50% traditional Search for core terms and stability, 25-30% AI Max for expansion and discovery, 20-25% Performance Max for multichannel reach. This hedges against the weaknesses of any single automated solution while capturing the benefits of each. AI Max will discover high-converting queries you'd never think to target manually. It will also burn budget on irrelevant clicks if you don't actively manage it. Both statements are true.

Google's push toward AI-powered advertising is inevitable—AI Max is just one step in that direction, alongside Smart Bidding Exploration and the broader automation of paid search. The question isn't whether to adopt AI tools, but how to do so strategically while maintaining human oversight and accountability. Test AI Max with realistic expectations, monitor performance honestly, and scale only what delivers measurable incrementality. That's how you succeed with AI Max in 2025, regardless of what Google's marketing materials promise.

Frequently Asked Questions