Google Ads for AI Search: Types, Examples, & Cost

Google Search is entering a new era.

For more than two decades, advertisers relied on a familiar model. Users typed keywords into Google, reviewed a list of search results, clicked a website, and eventually converted into customers. Google Ads evolved around that behavior, with formats such as Search Ads, Shopping Ads, Display Ads, and Video Ads helping businesses reach people at various stages of the buying journey.

Today, that model is changing.

With the rollout of AI Mode, Google’s Gemini-powered search experience is becoming more conversational, personalized, and context-aware. Instead of simply returning a list of links, AI Mode can answer complex questions, provide recommendations, compare products, and help users make decisions directly within Search.

This shift is creating an entirely new category of advertising.

At Google Marketing Live 2026, Google announced several new ad formats specifically designed for AI-powered search experiences. These formats go beyond traditional keyword-based advertising by integrating ads directly into conversational interactions, AI-generated recommendations, shopping experiences, and lead generation workflows.

For marketers, ecommerce brands, SaaS companies, agencies, and local businesses, understanding these new AI Search ad formats is becoming essential.

In this guide, you’ll learn:

• What Google AI Search Ads are
• How advertising works in AI Mode
• The different types of AI Search ads
• Real-world examples
• Cost considerations
• Best practices for advertisers

What Are Google AI Search Ads?

Google AI Search Ads are advertising formats designed specifically for AI-powered search experiences.

Unlike traditional search ads that appear above or below organic search results, AI Search Ads can appear directly within conversational responses, recommendation lists, shopping experiences, and AI-assisted decision-making journeys.

These experiences are powered by Gemini, Google’s family of advanced AI models.

The goal is not simply to show an advertisement.

Instead, Google is attempting to help users discover products and services that fit their specific needs while maintaining transparency about sponsored content.

According to Google, these ad experiences remain clearly labeled as sponsored while providing more helpful context than traditional ads.

This is an important distinction.

Historically, advertisers created ad copy and landing pages designed to persuade users to click.

In AI Search, Google increasingly helps users understand why a product, service, or offer may be relevant before the click even happens.

As a result, advertising is becoming more integrated into the research process itself.

How Google Ads Work in AI Mode

To understand AI Search advertising, it helps to understand how AI Mode works.

Traditional search follows a relatively simple process:

1. User enters a query.
2. Google identifies relevant results.
3. Search Ads compete in an auction.
4. User clicks a result.

AI Mode introduces a more sophisticated process.

A user may ask:

I’m planning a trip to Italy and want the easiest language-learning app for beginners. Which one should I choose?

Instead of displaying a list of blue links, Gemini can:

• Understand the context.
• Identify the user’s goal.
• Compare available options.
• Generate recommendations.
• Suggest follow-up questions.

This creates opportunities for advertisers to appear naturally within the research experience.

Google’s new AI Search ad formats are designed to fit within this conversational workflow.

Rather than interrupting the experience, these ads aim to contribute useful information that helps users make decisions.

One of the most significant changes is the introduction of AI-generated ad explainers.

In certain AI Search experiences, Gemini can evaluate information about a product or service and generate an independent explanation that appears alongside sponsored content.

This additional context is designed to improve transparency and trust.

For advertisers, success will depend less on writing clever ad copy and more on providing accurate product information, compelling offers, and strong customer experiences that Gemini can understand and surface.

Why AI Search Advertising Is Different

Many marketers assume these new formats are simply updated versions of Search Ads.

That assumption is incorrect.

Traditional Search Ads are primarily keyword-driven.

AI Search Ads are intent-driven.

In traditional search, advertisers often focused on:

• Keywords
• Match types
• Bids
• Click-through rates

AI Search introduces additional layers such as:

• User intent
• Contextual understanding
• Conversational interactions
• Product relevance
• Offer quality
• Information completeness

This means advertisers must think beyond keyword targeting.

They must also optimize:

• Product feeds
• Merchant data
• Promotional offers
• Website content
• Customer experience signals

The better Gemini understands a product or service, the more likely it is to appear in relevant AI-assisted experiences.

Types of Google Ads for AI Search

Google has introduced several new ad formats specifically designed for AI Mode and AI-assisted search experiences.

These formats represent the next generation of search advertising.

Conversational Discovery Ads

One of the most significant announcements from Google Marketing Live 2026 was the introduction of Conversational Discovery Ads.

These ads are designed to answer highly specific questions asked within AI Mode.

Instead of showing a standard text advertisement, Gemini helps generate creative tailored to the user’s exact query.

For example, a user might ask:

I want my house to smell like a luxury spa or a rainy forest. What are some low-maintenance ways to make my home smell amazing?

Gemini can analyze the request and help surface sponsored products that match the user’s needs.

The advertisement may highlight specific features, benefits, and product characteristics relevant to the conversation.

A key component of Conversational Discovery Ads is the AI-generated explainer.

Rather than relying solely on advertiser-written messaging, Gemini evaluates information about the product or service and generates additional context that helps users understand why the recommendation may be relevant.

This creates a more informative and interactive advertising experience than traditional search ads.

Highlighted Answers

Another major advertising format introduced for AI Search is Highlighted Answers.

When people use AI Mode, they often receive a list of recommendations rather than a single answer. For example, a traveler planning an international trip might ask:

What are the best language-learning apps for a two-week trip to Japan?

Instead of presenting one recommendation, Gemini may generate a list of options based on features, pricing, ease of use, user reviews, and suitability for the specific situation.

With Highlighted Answers, highly relevant advertisers can appear directly within those recommendation lists.

This is a significant shift from traditional search advertising.

Historically, advertisers competed for visibility above or below organic results. In AI Mode, advertisers can potentially become part of the recommendation experience itself.

Google has stated that these placements will continue to be clearly labeled as sponsored. However, they are designed to feel more relevant because they appear within the context of an AI-generated answer.

Why Highlighted Answers Matter

Highlighted Answers solve a major challenge facing advertisers in AI-powered search.

As AI-generated responses become more comprehensive, users may click fewer traditional search results.

Advertisers need visibility within the answer experience itself.

Highlighted Answers provide that opportunity.

For businesses, this means success may depend on:

• Product relevance
• Data quality
• User satisfaction signals
• Offer competitiveness
• Brand trust

Rather than simply bidding on keywords, advertisers must provide information that helps Gemini understand why a product deserves inclusion in a recommendation set.

Example of a Highlighted Answer

Imagine a user searching:

What is the best budgeting app for freelancers?

Gemini may generate a list of recommendations that includes:

• App A
• App B
• App C

If an advertiser’s product qualifies, it could appear as a Highlighted Answer within that recommendation framework.

This creates a much more contextual advertising experience than a traditional PPC ad.

AI-Powered Shopping Ads

Perhaps the most important AI Search advertising format for ecommerce brands is AI-Powered Shopping Ads.

Online shopping often involves extensive research.

Consumers compare:

• Features
• Prices
• Reviews
• Brands
• Product specifications

Google’s new AI-powered shopping experience aims to simplify that process.

Instead of forcing users to compare dozens of product pages, Gemini can evaluate products and generate personalized explanations.

How AI-Powered Shopping Ads Work

Suppose a user searches:

Best espresso machine for a small apartment under $500.

In a traditional search environment, the user would see:

• Search Ads
• Shopping Ads
• Organic listings

In AI Mode, Gemini can evaluate available products and generate customized recommendations.

The system may explain:

• Why a product is suitable
• Which features are most relevant
• How products compare
• What tradeoffs buyers should consider

At the same time, sponsored products can appear within the experience.

The result is a more informed buying journey.

The Role of Product Data

AI-Powered Shopping Ads depend heavily on structured product information.

Advertisers must provide accurate data through:

• Product feeds
• Merchant Center
• Product descriptions
• Pricing information
• Availability data
• Product attributes

Gemini relies on this information to generate explanations and recommendations.

This means product feed optimization becomes even more important than it is today.

Why AI Shopping Changes Ecommerce Advertising

Traditional Shopping campaigns focused heavily on:

• Product titles
• Product categories
• Bid strategies

AI-powered shopping introduces additional considerations.

Advertisers must ensure:

• Product information is complete
• Features are clearly described
• Pricing is accurate
• Inventory is updated
• Brand messaging is consistent

The more effectively Gemini can understand a product, the greater the likelihood it will appear in relevant AI-assisted shopping experiences.

Business Agent for Leads

Lead generation is another area being transformed by AI Search.

One of Google’s most innovative new formats is Business Agent for Leads.

This format replaces traditional lead forms with conversational interactions powered by Gemini.

The Problem with Traditional Lead Forms

Traditional lead generation often follows this process:

1. User clicks an ad.
2. User fills out a form.
3. Business follows up later.

While effective, this process has several limitations.

Users may:

• Leave the page
• Abandon the form
• Lose interest
• Forget to respond

Business Agent for Leads aims to reduce these friction points.

How Business Agent for Leads Works

Instead of filling out a static form, users can interact with an AI-powered brand representative directly within the ad experience.

For example, a prospective university student might ask:

What scholarships are available?

Or:

What are the admission requirements?

The Business Agent can provide answers based on information from the institution’s website.

This creates a more engaging and immediate experience.

Benefits of Business Agent for Leads

For users:

• Faster answers
• Reduced friction
• Better research experience

For businesses:

• Higher engagement
• Better lead qualification
• Improved conversion potential
• More meaningful customer interactions

Conversational Lead Generation

Business Agent for Leads represents a broader trend toward Conversational Lead Generation.

Rather than collecting information first and answering questions later, businesses can begin helping potential customers immediately.

This approach aligns closely with the way people naturally interact with AI assistants.

Direct Offers

Beyond new ad formats, Google is also expanding Direct Offers, a program designed to surface highly relevant promotions during AI-assisted shopping experiences.

Direct Offers were initially introduced as a pilot program, but Google has expanded the initiative significantly.

The goal is simple.

Help shoppers discover relevant deals while they are actively researching products and services.

Instead of forcing users to hunt for discount codes or special offers, AI Search can surface promotions at the moment they are most useful.

For advertisers, Direct Offers create a new opportunity to influence purchase decisions during high-intent research sessions.

Unlike traditional coupon campaigns, Direct Offers are designed to integrate naturally into AI-generated recommendations and shopping journeys.

As AI-assisted commerce continues to evolve, promotional visibility may become just as important as keyword visibility.

In the next section, we’ll cover Promotion Bundling, Native Checkout, Universal Commerce Protocol (UCP), travel-specific AI Search advertising, and the cost structure of Google AI Search Ads, including CPC, CPA, ROAS, and budgeting considerations.

Promotion Bundling

One of the most overlooked developments in Google’s AI Search advertising ecosystem is Promotion Bundling.

Traditionally, advertisers upload promotions individually. These promotions may include:

• Discounts
• Coupon codes
• Free gifts
• Buy-one-get-one offers
• Free shipping incentives
• Seasonal deals

The challenge is that a single promotion may not be relevant to every shopper.

Google’s new Promotion Bundling capability uses Gemini to dynamically construct offers based on a person’s search intent and shopping context.

Instead of displaying a static promotion, the AI can help create a more compelling offer from the advertiser’s available promotions.

How Promotion Bundling Works

Suppose a consumer is researching:

Best home gym setup for a small apartment

A retailer may have multiple active promotions:

• 10% off adjustable dumbbells
• Free resistance bands
• Free shipping
• Discount on workout benches

Rather than showing a single promotion, Gemini can evaluate available products and eligible offers to create a more attractive bundled deal.

This allows advertisers to present highly relevant incentives based on what shoppers are actively researching.

Why Promotion Bundling Matters

Consumers rarely evaluate products in isolation.

They compare:

• Features
• Pricing
• Value
• Included extras
• Available promotions

Promotion Bundling helps advertisers compete on value while reducing friction in the buying process.

For ecommerce brands, this could become one of the most powerful AI Search advertising features because it aligns offers with user intent rather than relying on static promotions.

AI Brief

Promotion Bundling is closely connected to another emerging concept called AI Brief.

Google allows advertisers to define:

• Products
• Eligible promotions
• Business rules
• Offer constraints

Gemini then uses this information to determine which offers should appear for specific search experiences.

Think of AI Brief as a strategic layer between the advertiser and Google’s AI systems.

Rather than manually building thousands of promotional combinations, advertisers establish guidelines and allow Gemini to optimize offer presentation.

As AI Search evolves, AI Brief may become an important component of campaign management.

Native Checkout

Another major innovation announced for AI Search is Native Checkout.

Historically, the customer journey often looked like this:

1. Search for a product.
2. Click an advertisement.
3. Visit a website.
4. Add a product to cart.
5. Complete checkout.

Every additional step creates friction.

Consumers may:

• Abandon their carts
• Leave the website
• Compare competitors
• Delay the purchase

Native Checkout aims to simplify this process.

What Is Native Checkout?

Native Checkout allows shoppers to secure promotions and complete purchases more directly within Google’s ecosystem.

Instead of navigating through multiple pages, users can move more efficiently from discovery to purchase.

This is particularly important in AI-assisted shopping experiences where users are already receiving product recommendations and promotional offers.

The goal is simple:

Reduce friction and increase conversion rates.

Benefits for Advertisers

Native Checkout can potentially improve:

• Conversion Rate
• Customer experience
• Purchase completion rates
• Revenue generation
• Return on Ad Spend (ROAS)

For advertisers, reducing the number of steps between product discovery and purchase often leads to stronger campaign performance.

Universal Commerce Protocol (UCP)

Native Checkout is supported by Universal Commerce Protocol (UCP) integrations.

Universal Commerce Protocol is designed to make ecommerce transactions more seamless across platforms and digital experiences.

In practical terms, UCP helps merchants connect product inventory, pricing, availability, and purchasing workflows with Google’s commerce ecosystem.

Why UCP Matters

As AI Search becomes more commerce-focused, users increasingly expect immediate action.

They do not simply want information.

They want outcomes.

Examples include:

• Booking a hotel
• Purchasing a product
• Reserving a service
• Claiming a promotion

Universal Commerce Protocol helps support these actions by connecting AI-assisted discovery with transaction capabilities.

Businesses that adopt UCP-enabled commerce workflows may be better positioned to benefit from future AI Search innovations.

Travel Expansion in AI Search

Travel is another category receiving increased attention within Google’s AI-powered advertising ecosystem.

Travel planning is naturally conversational.

People often ask questions such as:

What is the best family vacation destination in Europe?

Or:

Where should I stay in Tokyo for five days?

Or:

What is the most affordable beach destination for a honeymoon?

These queries involve multiple considerations.

Users evaluate:

• Destinations
• Hotels
• Flights
• Activities
• Budget constraints
• Timing

AI Search is particularly well-suited for these complex research journeys.

AI-Assisted Travel Planning

Google is expanding promotional capabilities for travel advertisers so that offers can appear directly within AI-assisted trip planning experiences.

Travel partners can potentially surface:

• Hotel promotions
• Travel discounts
• Package deals
• Seasonal offers
• Destination-specific incentives

This creates opportunities for brands to reach consumers during the decision-making stage rather than after they have narrowed their choices.

Why Travel Advertisers Should Pay Attention

Travel purchases often involve:

• Long consideration periods
• Multiple searches
• Extensive comparison shopping

AI Search helps consolidate that research process.

Advertisers that integrate promotions into AI-assisted planning experiences may gain an advantage over competitors relying solely on traditional search advertising.

How Much Do Google AI Search Ads Cost?

One of the most common questions advertisers ask is:

How much do AI Search Ads cost?

The answer is more complex than many marketers expect.

Google has not introduced a separate pricing system specifically for AI Search inventory.

Instead, costs are influenced by the same auction dynamics that govern other Google Ads placements.

These factors include:

• Competition
• User intent
• Industry
• Audience quality
• Conversion likelihood
• Ad relevance

However, AI Search inventory introduces new considerations.

Because these ad formats appear in high-intent conversational environments, competition may eventually become more intense than traditional search placements.

Cost Per Click (CPC)

Cost Per Click remains one of the most commonly used advertising metrics.

CPC measures the amount paid when a user clicks an ad.

Several factors influence CPC:

• Industry competition
• Search demand
• Product category
• Audience targeting
• Geographic targeting

Highly competitive sectors such as:

• Legal services
• Financial services
• Insurance
• Enterprise software

typically experience higher CPCs.

Cost Per Acquisition (CPA)

CPA measures how much it costs to generate a lead or customer.

For many advertisers, CPA is more important than CPC.

A campaign generating cheaper clicks is not necessarily more profitable.

If higher-quality AI Search placements produce better leads, advertisers may be willing to pay more per click in exchange for stronger conversion performance.

Return on Ad Spend (ROAS)

ROAS remains one of the most important profitability metrics for ecommerce advertisers.

As AI-powered shopping experiences become more prevalent, advertisers should focus on:

• Revenue generated
• Profitability
• Conversion quality
• Customer lifetime value

rather than simply pursuing the lowest CPC.

In the next section, we’ll cover AI Max for Search, AI Max for Shopping, advertiser best practices, common mistakes, future trends, and how businesses should prepare for the next generation of AI-powered search advertising.

AI Max for Search and AI Max for Shopping

While much of the attention surrounding AI Search advertising focuses on new ad formats such as Conversational Discovery Ads and AI-Powered Shopping Ads, Google has also introduced new campaign optimization layers designed to help advertisers participate more effectively in AI-driven search experiences.

Two of the most important are:

• AI Max for Search
• AI Max for Shopping

Google has positioned these solutions as foundational technologies for advertisers that want to maximize visibility across AI-powered search environments.

What Is AI Max for Search?

AI Max for Search is designed to help advertisers improve performance across increasingly complex search journeys.

Traditional search campaigns were built around keyword targeting.

Advertisers would:

1. Research keywords.
2. Create ad groups.
3. Write ads.
4. Manage bids.

AI-powered search changes this model.

People now search using:

• Questions
• Conversations
• Comparisons
• Research-driven prompts
• Multi-step decision journeys

As a result, relying exclusively on keyword matching becomes less effective.

AI Max for Search helps advertisers adapt by leveraging Google’s AI systems to better understand user intent and match ads to relevant opportunities.

Benefits of AI Max for Search

Advertisers can potentially improve:

• Reach
• Relevance
• Conversion volume
• Search coverage
• Customer acquisition efficiency

This becomes especially important as AI Mode continues to expand.

What Is AI Max for Shopping?

AI Max for Shopping focuses on ecommerce performance.

Shopping behavior is becoming increasingly conversational.

Consumers may ask:

Which laptop is best for graphic design under $1,500?

Or:

What espresso machine is easiest to clean?

Or:

Which stroller is best for travel?

AI Max for Shopping helps merchants participate in these AI-assisted shopping journeys by improving how products are surfaced and evaluated.

Key Inputs

AI Max for Shopping relies heavily on:

• Product feeds
• Merchant Center data
• Product attributes
• Inventory information
• Promotional offers

Advertisers with high-quality product data will likely see stronger performance than advertisers with incomplete or inaccurate feeds.

Best Practices for Google AI Search Advertising

Many of the tactics that worked in traditional PPC remain important.

However, AI Search introduces new requirements.

The following best practices can help advertisers prepare.

Focus on Search Intent Instead of Keywords

One of the biggest mistakes advertisers make is treating AI Search as a keyword expansion of traditional search.

It is not.

AI Search is fundamentally intent-driven.

Instead of targeting only:

• CRM software
• Project management software
• Marketing automation

Advertisers should think about:

• Customer goals
• Customer challenges
• Customer questions
• Decision-making factors

The better your content and product information align with intent, the easier it becomes for Gemini to understand relevance.

Improve Product Data Quality

For ecommerce advertisers, product information has become a competitive advantage.

Ensure your product data includes:

• Accurate titles
• Detailed descriptions
• Product specifications
• Availability information
• Pricing accuracy
• Category data

Incomplete product information limits Gemini’s ability to generate useful recommendations.

Optimize Merchant Center Feeds

Many advertisers underestimate the importance of feed optimization.

Strong Merchant Center data helps Google understand:

• Products
• Brands
• Features
• Categories
• Promotions

This information powers many AI-assisted shopping experiences.

Invest in First-Party Data

As advertising becomes more AI-driven, first-party data becomes increasingly valuable.

Examples include:

• Customer lists
• Purchase history
• Loyalty program data
• Website visitor data
• CRM data

First-party data helps advertisers provide stronger audience signals while reducing dependence on third-party sources.

Create Better Offers

AI Search places significant emphasis on usefulness.

The strongest advertisers often provide:

• Meaningful discounts
• Valuable bundles
• Competitive pricing
• Strong customer experiences

Promotion quality may become increasingly important as Direct Offers and Promotion Bundling expand.

Common Mistakes to Avoid When Running AI Search Advertisements

Businesses entering AI Search advertising often make several avoidable mistakes.

Treating AI Search Like Traditional PPC

This is perhaps the biggest error.

Many advertisers assume AI Search is simply another version of Search Ads.

In reality, conversational search introduces new behaviors and decision-making patterns.

Advertisers must optimize for context, intent, and relevance.

Ignoring Product Feed Optimization

AI-powered shopping experiences depend heavily on product information.

Weak feeds often result in weaker visibility.

Advertisers should continuously improve:

• Titles
• Descriptions
• Images
• Product attributes
• Availability data

Focusing Only on Clicks

Clicks remain important, but they are no longer the primary measure of success.

AI Search may influence users long before a click occurs.

Advertisers should monitor:

• Conversions
• Revenue
• ROAS
• Lead quality
• Customer acquisition

instead of focusing exclusively on traffic volume.

Underestimating Conversational Journeys

Consumers rarely make decisions after a single question.

• They research.
• They compare.
• They ask follow-up questions.
• They evaluate alternatives.

Advertisers should create assets that support the entire decision-making process rather than targeting a single interaction.

The Future of Advertising in AI Search

Google’s latest announcements provide a glimpse into where search advertising is heading.

Several trends are becoming increasingly clear.

Conversational Commerce

Search is evolving into a commerce platform.

Instead of searching, clicking, and buying through multiple systems, users can increasingly:

• Research
• Compare
• Evaluate
• Purchase

within a connected experience.

This trend will likely accelerate over the next several years.

AI-Powered Product Recommendations

Gemini is becoming more capable of understanding products, services, customer needs, and purchase intent.

As recommendation quality improves, advertisers will need to compete based on:

• Relevance
• Product quality
• Offer strength
• Customer satisfaction

rather than solely on bidding strategies.

Agent-Based Buying Experiences

Future AI systems may help users:

• Compare products
• Book services
• Schedule appointments
• Complete purchases

with minimal manual effort.

This could dramatically reshape customer acquisition strategies.

More Integrated Transactions

Native Checkout and Universal Commerce Protocol suggest that Google is moving toward more seamless commerce experiences.

Reducing friction between discovery and purchase remains a major opportunity.

Advertisers that embrace these systems early may gain a competitive advantage.

Frequently Asked Questions

What are Google AI Search Ads?

Google AI Search Ads are advertising formats designed for AI-powered search experiences such as AI Mode. These formats include Conversational Discovery Ads, Highlighted Answers, AI-Powered Shopping Ads, Business Agent for Leads, and Direct Offers.

Are AI Search Ads different from traditional Search Ads?

Yes. Traditional Search Ads primarily rely on keyword targeting, while AI Search Ads are more heavily influenced by user intent, conversational interactions, contextual relevance, and AI-generated recommendations.

What is the most important AI Search ad format for ecommerce brands?

AI-Powered Shopping Ads are currently among the most important formats because they integrate directly into AI-assisted product discovery and shopping experiences.

Do AI Search Ads cost more?

Not necessarily. Pricing is still influenced by auction dynamics such as competition, relevance, and conversion likelihood. However, high-intent AI Search placements may become more competitive over time.

What should advertisers do now?

Businesses should focus on:

• Improving product data
• Optimizing Merchant Center feeds
• Building strong promotional strategies
• Leveraging first-party data
• Preparing for AI-assisted commerce experiences

Final Thoughts

Google’s introduction of AI Search advertising marks one of the most significant changes in digital marketing since the launch of modern PPC advertising.

New formats such as Conversational Discovery Ads, Highlighted Answers, AI-Powered Shopping Ads, Business Agent for Leads, Direct Offers, Promotion Bundling, and Native Checkout signal a broader shift toward conversational commerce and AI-assisted decision-making.

For advertisers, success will increasingly depend on helping AI systems understand products, offers, and customer needs. The businesses that invest early in high-quality data, strong customer experiences, and AI-ready marketing strategies will be best positioned to succeed as AI Search continues to evolve.

The future of search advertising is no longer just about winning clicks. It is about becoming part of the conversation.