Over the past year, most AI conversations in marketing have centered on organic disruption. AI Overviews reshaped visibility. Chat-based discovery exploded. Publishers recalibrated. SEO teams hunkered down for the storm.
Paid search, meanwhile, felt comparatively stable. We continued optimizing feeds. Testing automation. Refining structure. Improving efficiency. The auction had inklings of evolution (AI Max for search or Ads in AI Overviews), but the core playbook held. With recent announcements from Google and OpenAI, one thing is clear: AI-driven discovery is evolving into AI-driven commerce through paid search ads in LLMs.
Ad formats continue to evolve. Measurement frameworks remain incomplete. But the infrastructure is being built. And that infrastructure will determine where monetization goes next.
From Search Results to Synthesized Answers
Traditional paid search is built on a familiar structure:
User submits a query → Google returns results → advertisers compete in the auction → user clicks.
LLMs change both the middle of that equation and where it happens. Instead of ten links and multiple ads, users receive a synthesized answer. Sometimes a shortlist. Sometimes a recommendation. Sometimes, a nearly complete decision path.
The monetization challenge shifts from page placement to integration: How does an ad appear inside a trusted answer flow without disrupting credibility?
That challenge explains why paid has not been disrupted as quickly as organic. Trust is central to these AI systems. Monetization has to be engineered carefully. But recent signals tell us that engineering is already underway.
At the same time, the direction is clear. Google’s Agentic Commerce and Universal Commerce Protocol are building the connective layer between AI systems and merchant data such as pricing, availability, inventory, and transaction capability. OpenAI is testing ads inside ChatGPT with limited measurement and clearly labeled placements. Perplexity has experimented with advertising and then stepped back due to concerns around trust and subscription growth.
These platforms are gradually creeping from answer engines to transactional environments. They also understand that monetization has to be rolled out carefully. And we see exactly that with ChatGPT:
- Early formats are structured
- Measurement is minimal
- User and advertiser adoption is limited
That tells me 3 things: transactions are coming, the rollout will be calculated, and that is where paid re-enters the picture in a more familiar, meaningful way.
What Should Advertisers Do Now?
For the past year, many paid teams have felt like sideline superfans to our organic superstar players. Organic visibility shifted quickly as AI Overviews expanded, conversational interfaces gained adoption, and as many as 37% of searches began in AI tools. On the paid side, the fundamentals remained steady, but that doesn’t mean they should be ignored!
The move right now is not to chase immature ad placements, unless your wallet allows. It is to strengthen the elements of your paid search playbook that will translate directly into AI-driven environments.
1. Treat Feed Excellence as a Competitive Advantage
If AI systems begin recommending products inside answer flows, structured product data determines eligibility. Ad copy and bid adjustments continue to play a role, but structured inputs ultimately shape how AI systems interpret your product. If commerce becomes shortlist-based, the feed determines whether you are considered at all.
Paid teams should be auditing:
- Titles aligned to real user language, not internal SKU naming
- Rich, structured attributes (category, material, compatibility, size, use case)
- Accurate pricing and availability signals
- Clean variant mapping
- High-quality imagery
- Consistent taxonomy across the site and Google Merchant Center
Google’s commerce infrastructure direction reinforces this. AI systems rely on standardized, interpretable data. When feeds are inconsistent or incomplete, AI systems default to cleaner alternatives.
Your feed is your golden ticket for e-commerce LLM readiness.
2. Test the Automation Tools That Already Exist
Before ads fully mature inside LLMs, Google is already shifting paid search toward automation and intent interpretation through:
- AI Max for Search
- Broad Match (with guardrails)
- Performance Max
- Demand Gen
These tools reflect how platforms interpret intent today. They provide a preview of how auctions behave when machine learning weighs signals more than manual structure.
Teams that actively test Broad Match with disciplined negative strategies, refine Performance Max through feed control, and evaluate AI Max thoughtfully are building skill sets aligned with where the auction is heading. Automation only works when it’s guided carefully. Strong inputs improve results, and weak structure gets exposed quickly. The advertisers who understand how to guide machine learning now will adapt more fluidly when AI monetization expands into those conversational environments.
3. Recognize the Funnel Is Compressing
Paid search has historically excelled at harvesting demand at the moment of conversion. LLMs compress comparison behavior. Fewer searches. Fewer clicks. Shorter paths. That means paid teams need to think beyond pure last-click capture.
Leaning into Shopping and Performance Max is not just about scale. It’s about ensuring your product data is accessible wherever Google decides to surface it, whether that’s a traditional SERP, AI Overview, or a conversational interface (coming soon).
4. Expect Trust to Shape Early Ad Formats
Perplexity’s decision to stop testing ads underscores how fragile trust is in AI environments. OpenAI’s language around clearly labeled, separate ad placements reinforces that early formats will likely be structured and visibly sponsored.
Translation for paid teams:
- Early measurement will be limited
- Early CPMs are high (starting at $60 for ChatGPT)
- Early inventory may skew upper-funnel
That doesn’t mean ignore it. It means evaluate it through a strategic lens, not hype.
The platforms are not going to jeopardize user trust for short-term ad dollars (or will they?). That buys advertisers time to build strength in the fundamentals.
The Bottom Line
Organic disruption captured headlines first. Now we are starting to see paid search take center stage in industry news.
Google and OpenAI are building connective tissue between AI answers and commerce. As that integration deepens, structured data, automation fluency, and thoughtful testing will influence who appears inside AI-driven experiences. The question remains on how these ads will surface on a large scale and which brands are prepared when they do.
The advantage will go to brands that strengthen their foundations, test intentionally, and adapt as the rules evolve.
Interested in getting your ads in front of searchers in AI tools? Let’s talk about next steps, or you can connect with us on LinkedIn for more educational content about paid search and AI tools.
