The online advertising industry is changing fast, and one of the largest game-changers is the incorporation of Artificial Intelligence (AI) in search engines. Google, being a leader in the search sector, has launched AI-based instruments such as the Search Generative Experience (SGE) and AI-based chatbots. For advertisers, this presents a new universe of possibilities—and issues—regarding Pay-Per-Click (PPC) campaigns.

This manual contains everything you would want to know about the operation of PPCcampaigns in AI search engines, in particular Google AI Overviews, and via its chatbotfeature. Explaining how these function, strategy optimization across the new formatsfeatured in the ad campaigns, issues you may be experiencing, and what lies aheadin AI advertising.

1. The Evolution of Search and PPC Advertising

When compared to our previous sessions, we can now be in a better position after traversing the key stages of the evolution of pay-per-click (PPC) campaigns in and around Google.

The Early Years of Search Advertising (2000 – 2005)

In 2000, AdWords not only launched but was a simple, yet revolutionary concept for Google, filled with advertisers bidding on keywords, where ads were displayed next to the organic search results. These were text ads only, restrictive character count, and relied almost solely on exact keyword matching. There weren’t many competitors; almost any small business could bring in tons of traffic for just a few cents per click.

That was probably the point in time when the only thing that mattered was keyword visibility. The more the advertiser understood the types of phrases people were typing in their queries, the more successful their campaign would be. Core targeting features, apart from basic keyword bids for display, were quite limited, making it a simple yet restricted system.

The Growth and Transition (2006-2012)

As the number of internet users exploded, Google began using quality-based ranking. This meant it was no longer just about a bidding game to focus on quality, relevance, and click rates. You now had a Quality score, which became the only measure to balance ad spend and ad quality.

It was during this timeframe that we started to see the following:

  • Expanded Text Ads: Ads, now from a headline, have turned to additional lines of copy for more flexibility on messaging. 
  • Product Listings (Google Shopping): Ads for easy-to-see products that included imagery, pricing, and merchant information for specifically e-commerce, were introduced.  
  • Geo-targeting and Language Targeting: Advertisers were able to filter campaigns by location and audience. The search strategies started to focus on local.

The trend was very clear-it was becoming more and more personal, more visual, and more competitive.

Diversification Across Formats (2013-2018)

By this time, search advertising had diversified itself through a variety of formats. Google integrated YouTube ads, display campaigns, app promotion ads, and remarketing into the same ecosystem. PPC advertising had moved away from being limited to search results and started encroaching on larger digital journeys.

Some of the impacting trends were:

  • Mobile-first campaigns: Smartphones have connected us so much that the speed and relevance of ad and marketing campaigns have become increasingly important.
  • Call extensions and ad extensions: Additional information, such as phone numbers, sitelinks, and reviews, added click-through potential.
  • Audience targeting: Advertisers could segment based on user behavior, interest, and demographics, beyond keywords.

Marketers also began to transition away from search-only campaigns into integrated digital ecosystems, in which search was part of a larger, cross-channel advertising campaign.

PPC Through Automation: The Age of Smarter Campaigns (2019-2023)

The age of artificial intelligence and machine learning has led to major shifts regarding the implementation of automation via PPC. Advertisers are now able to create responsive search ads, where Google can take various combinations for headlines and descriptions to see which will be the highest performing combination.

Additional advancements included:

  • Smart Bidding Strategies: Based on an algorithm in real time, the bidding was optimized for conversions or return on ad spend.
  • Dynamic Search Ads: An ad copy was auto-generated based on the content on the website.
  • Performance Max Campaigns: They advised the advertiser’s ability to run across all Google channels (Search, Display, YouTube, Discover, Gmail, Maps) with a single budget and auto-optimized.

All these advances lessened the hands-on management of the campaign, but also made it all less directly controllable for the advertiser to manage the blending of automation and strategy from the human side.

The Growth of More Contextual and Conversational Search (2024+)

Searches have shifted from a keyword-driven model to an intent-and context-driven one. Users today are searching naturally, in a conversational tone rather than typing short phrases. The traditional model of “10 blue links” is slowly evaporating now that the algorithm needs to serve results based on summarizing answers, visual content, product listings, and instant actions. 

As such, advertising is going to have to find its way into this. Rather than bidding on a keyword alone, advertisers will have to somehow predict user intent, stage of their journey, and form of content they want. Search ads are no longer competing for a click – they are competing to be the most relevant and reliable recommendation at the time of need.

2. What Are Google’s AI Overviews?

Google’s AI Overviews are a major change in how search results are served to users. Unlike traditional search result pages that primarily serve links to websites, AI Overviews serve information in summary form from multiple sources into 1 well-rounded response. This summary dichotomy is supposed to save you time and put the best and most relevant information right in front of you instead of having to click though multiple results pages.

For instance, if a user searches for “best ways to cook quinoa,” instead of listing blog or recipe sites, the AI Overview may generate a step-by-step cooking guide that synthesizes tips, measures, and techniques found in multiple trustworthy sources. The AI also frequently cites those original sites, so users have the option to investigate more.

Key Features of AI Overviews:

  • Synthesis Across Multiple Sources: The AI synthesizes content from multiple web pages, research articles, and authoritative sources into one summary. This reduces the work a user has to do sorting through search results to find multiple sources.
  • Contextual Relevance: AI Overviews analyze user intent based on the search query. The results would not just be based on a keyword, but they would also have context, phrasing, and inferred need.
  • Interactive Features: Overviews include expandable sections, links, or suggestions for follow-up questions that allow users to dive deeper into a particular piece of information without leaving the search page.
  • Dynamic Updates: These summaries will have been generated in real time, so they reflect the most current information that is available on the web. This can be very useful for quickly changing topics, such as technology, health advice, or news.
  • Embedded Images and Structured Data: AI Overviews can contain visuals, like images or tables, or other formats of a visual nature, which provide structured data on a site to enhance comprehension or interest.

Impact for Advertisers:

For brands and marketers, AI Overviews have implications for advertisers in how pay-per-click works in the traditional sense:

  • Change in Engagement: Users may read an overview of content as opposed to scrolling through links in the search results. This behavior would lower organic click-throughs for traditional search ads and change the analysis of the performance of those ads.
  • Non-Visible Ad Placements: This means that advertisers would need to adapt to remain visible. Google has indicated that it is testing sponsored product/service cards that are embedded in the AI Overviews. These ads will be created to fit seamlessly into the experience of reading a summary, because, even being sponsored, it can be annoying to distinguish between the summary content and the sponsored ad.
  • Contextual Advertising Opportunities: The AI Overviews are intent-driven, so ads placed within this high-value content can create targeted advertisements more valuable than regular keyword-driven search ad placement. Ads that are in a higher order of interest can have a perceived higher value.
    Need for Quality Content: Since AI is aggregating all the sources, organizations that produce high-quality, authoritative, detailed, and organized content are more likely to be cited in AI Overviews—benefiting their visibility and relevance to ads.
  • Impact on SEO/PPC Strategy: With AI Overviews influencing how marketers determine organic results, there will be a diminished need for marketers to rely on organic rankings in the future. Marketers must ensure their PPC campaigns align with the content AI will likely aggregate. High-quality content, structured data, and clear product and service offerings will aid in more effective ads.

Simply put, AI Overviews are not just a new way for users to consume information. They also indicate a shift in strategy for brands to respond to search users. Ads are no longer confined to only the traditional ad spot in the sidebar or above search results and are becoming integrated into the summarized content experience. Brands will need to develop effective targeting, messaging, and creative approach to align with how AI summation is returning in info.

3. How Pay-Per-Click Advertisements Function in Enhanced Search Experiences and Chat Interfaces

When individuals search online, they tend to look for quick and short responses rather than scrolling through multiple links. To this end, Google and other search platforms have started providing summarized information and interactive search results, and they are changing how ads are displayed.

This is how Pay-Per-Click (PPC) ads can appear in contextually relevant placements that support the content users are accessing, rather than simply appearing at the top or the bottom of a page. Ads are embedded within the content or delivered in product/service cards next to friendly summaries.

Contextual Ad Placement Examples

  1. Guided recommendations:
  • A user searches for “best running shoes for flat feet.”
  • Search results show a brief guide on features, pros, and cons for running shoes.
  • The guide includes sponsored product cards for brands, so the user can click to shop.
  1. Interactive Queries:
  • People may ask follow-up queries such as, “Where do I buy these shoes?” or “What are the prices for these models?”
  • PPC ads appear next to the answer, linking the user to an e-commerce store or product page to provide options for someone ready to shop.

Key Insights for Advertisers

  • Intent is more important than keywords: ads perform best when they are in sync with the user’s purpose or inquiry, as opposed to matching search queries only.
  • Ad formats integrated within the user experience: Images, product cards, and descriptive links are better performing when they are naturally integrated within the content or respond the user is reading. 
  • Higher engagement opportunities: Because ads are served at the moments users explore options or seek recommendations, ads tend to have higher click-through and conversion rates than traditional placements. 

In general, PPC advertising is moving beyond the simplified format of focusing on keywords and placing bids. Success increasingly depends on understanding user intent, relevancy of offers, and ad serving in conjunction with the content that users appear to be engaged with. 

4. Advantages of Advertising in AI Overviews

There are several advantages to running a PPC campaign in AI Overviews: 

More relevant:
Ad placements are offered directly in sync with user intent. For example, if a user is inquiring about types of insurance plans, the ad for an insurance company will be contextually included with the overview of what the user is looking at.

More engagement by user: Because AI Overviews are conversational and relevant to each unique user, ads may engage users more than traditional ad placement simply because they are part of the expected flow of information.

5. Barriers of AI-Driven PPC Ads

While there are opportunities, AI-generated ads have new challenges:

  • Less Chance for Clicks: Since the AI-generated overview summarizes articles, users may not scroll down to see standard ad placements as often.
  • Transparency of Ads: Differentiating AI-created experiences and paid ads could be difficult for the user.
  • Measurement of ROI: Tracking conversions, impressions, and clicks could be difficult in an AI-generated interface.
  • Competition for Space: Fewer spots will create competition, and cost will go up.

6. How to Execute PPC Campaigns in AI Overviews

To market successfully on Google’s AI Overviews, advertisers will have to think differently about the depth of the campaign structure and the optimization of it in future campaigns. Here are some key steps:

a. Keyword Strategy: Move From Broad Keywords to Intent Keywords

In AI-based search, bidding on ‘keywords’ in a traditional approach will take a less prominent role. Instead of being reliant on broad keywords, satisfy your keyword strategy by filling user intent with enriched phrases (longer, intent-style keywords that indicate they are ready to buy).
For example, 

Rather than having ads run on the keyword “running shoes,” it would be better to have ads run on “best lightweight running shoes for marathons.” 

This will improve the chances that your ad will be placed in the contextually relevant AI summary.

b. Structured Data and Feed

AI will be relying on structured data to pull accurate information. The more robust the information your product feeds, schema markup, and Google Merchant Center entries are, the better chance your ads will show in AI summary content.

c.  Ad Copy that is Contextually Conversational.

Because ads will be shown in the context of AI summaries (conversational), your ad copy should be:

– to the point and informative.

– conversational in tone.

– solution-oriented to the user’s query.

d. Readiness for Visual & Product Cards

Google is highlighting visual ad formats (for example, product cards with images, ratings, and prices). Ensure that your assets are high-quality, mobile optimized, and visual assets are relevant to get noticed in AI interfaces.

e. Changes in Bids and Budgets

With fewer placements with higher value, CPCs may increase. Marketers should:

Increase budgets on unicorn/ high-intent campaigns.

Utilize AI bid strategies like Maximize Conversions and Target ROAS.

f. Preparing to Test Conversational Ad Extensions

As interactions in chatbots increase, Google may move to offer conversational ad formats, such as clickable call-to-action buttons within the chat flow. Marketers should be ready to test and optimize these upcoming formats.

7. Tracking and Analytics in AI Ads

Measuring in AI search engines will mean a different look and methods. Traditional measures of measurement, like impressions and CTR, may be harder to isolate.
In the meantime, focus on the following measures:

  • Engagement Metrics: The engagement with AI-served ads.
  • Attribution Modeling: Multi-touch attribution of discoverability via AI.
  • Conversion Tracking: Triage AI ad experience to a purchase or lead.

Google may soon offer updated analytics to measure performance to track in the AI Overview, so marketers need to be familiar with this platform.

While the combination of search and AI is still in early stages, we identify some trends:

  1. Fewer Ads but More Valuable Ads – The scarcity of ads will increase competition and raise CPC.
  2. Conversational Commerce – Chatbots will assist navigation and conversions.
  3. Deeper Personalization – Ads will become hyper-relevant based on browsing behavior, history, and context.
  4. Critical First Mover Advantage – Adopters of AI-based PPC will have a leg-up on the learning curve with lower competitors

9. Useful Advice for Marketers

Stay on top of Google announcements about ads with AI.

  • Regularly update product feeds and structured data.
  • Gradually shift budgets to test AI Overview placements.
  • Experiment with conversational search ad creatives.
  • Leverage audience insights to optimize targeting.

10. Conclusion

AI search engines, especially Google’s AI Overviews and chat functionalities, are the next digital advertising frontier. For PPC marketers, success will be based on translating strategies from keyword bidding to intent-based, conversational, and contextual ads. Challenges do abound — from constrained placements to intricate tracking — but hyper-relevance and greater engagement assure it as the key channel for future growth.

Those who invest early in learning how to optimize their PPC campaigns for AI search will not only gain a competitive advantage but also future-proof their ad strategies in a rapidly changing digital environment.