Google Ads AI Max explained

With the launch of AI Max in May 2025, Google Ads promised to change how we manage search campaigns by leveraging AI. This new feature has sparked mixed opinions in the industry. While some report significant performance improvements, others remain cautious. 

At Flowboost, we've been testing AI Max, and while it has proven effective in some cases, it doesn’t always deliver consistent results as expected. In this article, we’ll break down what AI Max is, how it works, and when it can be useful to improve your campaign performance.

What is Google AI Max?

Google AI Max is an AI-powered upgrade designed to enhance Search campaigns by improving targeting, bidding, and asset optimization. It is not a new campaign type, but an additional layer that uses Google’s AI models to better understand user intent and improve ad performance.

Instead of relying mainly on traditional keyword matching, AI Max evaluates the context behind a search, such as meaning, intent, and past behavior. This allows campaigns to capture opportunities that might be missed when using a limited keyword list.

How AI Max works

AI Max enhances campaigns by focusing on three key areas:

• Query matching: AI Max interprets search intent beyond exact keywords. For example, a campaign targeting “running shoes” might also capture related searches like “best shoes for marathons” or “cushioned trainers,” even if these are not explicitly in the keyword list.

• Landing page expansion: AI Max can automatically direct users to alternative landing pages within your account if it determines that another page is more relevant to the search query. While this can improve relevance, it also introduces risk: the system may select pages that are not optimal for conversion or that advertisers did not intend to use. Because the platform does not always understand business priorities or funnel structure, this feature requires careful oversight.

• Asset optimization: AI Max dynamically adjusts ad assets based on the user’s search query. This can include rewriting or expanding ad copy to increase the likelihood of a click. However, this optimization is not always brand-safe. For example, the system may introduce messaging such as “cheap products” for premium or luxury brands if it predicts higher engagement. Without proper controls, this can conflict with brand positioning.

Across all three areas, AI Max can deliver strong results, but active management remains essential. Specialists should continuously monitor performance, review automated decisions, and apply exclusions or adjustments where needed.

While budgets, goals, and exclusions remain under advertiser control, AI Max independently expands queries and creates or selects new assets. This level of autonomy can improve efficiency and performance, but only when paired with regular monitoring to ensure campaigns align with expectations and brand strategy.

The advantages of using AI Max

AI Max can offer improvements for advertisers, but its effectiveness depends heavily on the account and context. It works best when campaigns already have a solid foundation, including well-structured accounts, reliable conversion data, and a thoughtful keyword strategy. Without these guardrails, results can be unpredictable.

1. Better coverage of relevant queries

AI Max goes beyond exact keyword matching and can help capture additional relevant searches that traditional methods might miss, including long-tail opportunities. However, this only works effectively when proper keywords, campaign structure, and the right guard rails are in place.

If your account is not yet using broad match keywords, we suggest to start with those first before enabling AI Max. As we see AI Max generally goes even a bit broader then broad match keywords.

2. Support for interpreting intent

For campaigns that already have a strong setup, AI Max helps interpret user intent and surface relevant queries that align with goals. This can reduce the chance of missing opportunities, but it is not a substitute for a complete keyword strategy.

3. Consistent performance with high-quality data

AI Max performs best in accounts with clean and stable conversion data. Well-maintained historical data allows bidding models to work more predictably, improving performance metrics like CPA or ROAS. While this is true for most smart bidding strategies, AI Max goes beyond that by optimizing ad creatives and expanding search query coverage based on user intent.

4. Adapting to changing search trends

AI Max enables campaigns to adapt to evolving search behaviour, especially as AI-driven experiences such as AI Overviews and AI Mode become more prominent. These environments introduce new ad placements that do not exist in traditional search results and require different matching and delivery mechanisms.

By enabling AI Max, advertisers make their campaigns eligible to appear in these emerging AI-powered placements. Without it, ads may be limited to classic search results, missing visibility in areas where users increasingly discover information. While AI Overviews and AI Mode are not yet showing ads in all markets, they are already live in others, making early adoption a strategic preparation rather than a reactive adjustment.

For this reason, testing AI Max now allows advertisers to build data, understand performance implications, and be ready as soon as these placements expand. This approach reduces dependency on last-minute changes and increases the likelihood of gaining early visibility compared to competitors when AI-driven ad formats become more widely available.

The Limitations and risks of AI Max

While AI Max offers many opportunities, it is not suitable for every campaign. Its effectiveness depends heavily on the account setup, campaign goals, and context. Understanding its limitations helps avoid disappointment and ensures better results.

1. Less control over targeting

AI Max relies on Google’s AI to interpret search intent, which reduces the level of precise control advertisers have over targeting. Ads may be shown for broader or unexpected search queries. For campaigns that require very specific targeting, this can be a drawback. It is important to weigh whether broader reach is more valuable than tight control.

2. Results may vary

AI Max does not guarantee consistent improvements for every account. Performance depends on factors like account setup, campaign structure, and the quality of conversion tracking. For some accounts, results may be less predictable, so it is important to monitor performance and make adjustments where needed.

3. Requires solid conversion tracking

Like any automated system, AI Max works best when conversion tracking is clear and accurate. This is true for the account as a whole, not just for AI Max, and ensures that bidding and asset optimization function properly.

4. Risk of over-reliance on AI-driven optimization

Although AI Max automates some processes, relying solely on AI can overlook important details. Creative assets may not always align perfectly with a brand’s tone or messaging. Manual review and adjustments are still recommended to maintain consistent brand representation.

5. Not suitable for all industries or objectives

AI Max tends to work best in higher-volume campaigns with sufficient data. For niche industries, small businesses, or campaigns with very specific goals, its broader approach may not achieve the desired performance.

When AI Max is (and isn’t) a good fit

AI Max has the potential to significantly impact Google Ads campaigns, but its effectiveness is highly dependent on the specific account setup, structure, and objectives. At this stage, AI Max should be viewed as an early-phase product rather than a fully mature solution.

This situation is comparable to the early days of Performance Max. Initially, Performance Max delivered mixed results and required experimentation, learning, and clear guardrails before it became a reliable component of many advertising strategies. Over time, and depending on how it is implemented, it has proven useful in certain contexts.

The same applies to AI Max. Current observations are based on its present capabilities and behaviour, which are still evolving. As Google continues to develop AI Max, its performance, level of control, and use cases are likely to change. For now, it is best approached as a feature to test, evaluate, and monitor carefully, rather than as a universal solution that can be broadly recommended without account-specific expertise.

When AI Max is a good fit

AI Max works best in accounts that have solid campaign structure, accurate conversion tracking, and sufficient historical data. It can help capture long-tail queries and high-intent searches that might be overlooked by traditional keyword targeting. Campaigns with enough scale and flexibility to adapt to broader targeting strategies are likely to benefit the most.

When AI Max isn’t a good fit

AI Max may be less suitable for accounts with low investment levels (for example, under €2,000 per month), limited or unreliable conversion data, or a strong reliance on highly precise keyword targeting. In these cases, the AI’s broader approach may not align with campaign goals, making close manual monitoring and ongoing adjustments essential.

How to test AI Max safely

Testing AI Max is essential to understand how it affects your Google Ads campaigns. Because it automates many processes, careful testing is necessary to avoid risks like overspending or skewed metrics.

• Use controlled experiments: Run side-by-side campaigns to compare AI Max with traditional manual management. Track key performance indicators such as CTR, conversion rate, and ROAS to see how AI Max behaves in your specific account and industry.

• Monitor performance closely: Keep a close eye on results during the test phase. Even though AI Max adjusts bids and assets automatically, you should ensure that performance aligns with campaign goals and that no undesired behaviors occur.

• Ensure clear conversion tracking: Check that conversion tracking is accurate and reliable before testing. High-quality conversion data allows AI Max to optimize more effectively and make smarter decisions.

• Scale gradually: After successful small-scale tests, increase budgets and campaign size step by step. This maintains control while letting AI Max optimize performance over time.

By following these testing guidelines, you can safely explore the potential of AI Max while minimizing risks. 

Final thought

At its current stage, AI Max remains largely unpredictable for most Google Ads accounts. Its behaviour and performance can vary significantly depending on account structure, data quality, and campaign setup. For this reason, AI Max should not be approached as a guaranteed improvement, but as a feature that requires thorough and controlled testing.

That said, the time to start testing is now. It is only a matter of time before ads appear within AI Overviews and AI Mode, and advertisers who wait risk falling behind competitors who are already experimenting and learning. Being prepared matters more than achieving immediate wins.

A cautious, structured approach is recommended. Start with a limited selection of campaigns that already use broad match. Run controlled experiments to understand impact, isolate results, and gather insights. If initial tests are successful, scaling can follow. If results are inconclusive or negative, AI Max should not be switched off immediately. Instead, alternative setups and methods should be tested, as long-term participation in these AI-driven placements will likely become essential for visibility.

In short, AI Max is not yet predictable — but avoiding it altogether is no longer a realistic option. Testing, learning, and adapting now is the safest path forward.