OpenAI and Google unveil competing ideas for AI ads

Google and OpenAI executives recently sketched out the future of advertising — and they look very different

The next phase of digital advertising will not be fought for on the search results page alone. It builds in AI for chat conversations and commercial prediction engines. This week, both OpenAI and Google provided new details about how they plan to integrate advertising into their AI experiences — and the differences are revealing.

Here’s what marketers need to understand.

The OpenAI approach: Ads that feel like answers

On the OpenAI podcast, OpenAI CEO Assad Awan shared some new information about how ads can work within ChatGPT. The company is clearly trying to avoid the mistakes of early display advertising. The bottom line: ads should feel like useful extensions of the conversation, not distractions.

Instead of the usual placement of banners or transparent sponsored blocks, Awan described a model where ads appear as clearly labeled sponsored responses that match the context and user’s question. If someone asks for recommendations for accounting software or running shoes, for example, an advertiser might appear within the answer – but in a way that matches the tone and structure of the assistant.

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Awan emphasized three lines of caution:

• Clear labeling so users understand what is sponsored.
• Compatibility based on the user’s current query.
• There is no use of private conversations to target ads.

In other words, OpenAI is trying to design interactive ads instead of digital billboards.

A broad definition is important. If ChatGPT becomes the primary interface for discovery, ads won’t compete for pixel space. They will compete for confidence within the answer. That raises a new optimization question: How do you create sponsored content that feels truly useful within AI-generated feedback?

The Google approach: AI is everywhere, but commercialization first

Google, meanwhile, has laid out its 2026 roadmap for digital advertising and commerce — and is doubling down on the integration of AI across its ad stack.

In his third annual book, Vidhya Srinivasan, Google’s VP and GM of Ads and Marketing, explained how Search, YouTube, and its shopping infrastructure are being rebuilt in the age of engineering — where AI doesn’t just surface information but actively assists, recommends and completes transactions.

Srinivasan previewed the intensive use of AI in campaign automation, target audience prediction and creative. Performance Max continues to evolve towards autonomous use, AI decides where and how to allocate budget across Search, YouTube, Shopping and Display.

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But it’s a great commercial signal.

Google relies heavily on product discovery including AI Overview, shopping ads and merchant data feeds. Expect more AI-generated summaries, personalized product recommendations and things to buy embedded directly into search and YouTube.

In other words, Google’s strategy is keeping ads rooted in its existing ecosystem — but making AI an optimization engine under the hood.

Two models, two philosophies

OpenAI is experimenting with native chat placement within the chat interface. Google is putting AI into a mature ad infrastructure.

The challenge for OpenAI will be monetization without destroying trust. If ChatGPT’s ads sound too invasive or too common, users may back off. If they feel useful and transparent, they can become a powerful new channel of action.

Google’s challenge is different. With AI Overview already searching for specific clicks, marketers are asking how visibility and attribution will work in a world where fewer users click through to websites. Google’s answer seems to be to consolidate the balance between AI results and commercial units – keeping transactions within its ecosystem.

What are the product changes

For marketers, this indicates a structural change.

First, the creative strategy must adapt to the conditions of the negotiations. Advertisements may read more like expert recommendations than promotional copy.

Second, first-person data and feed for organized products is very important. AI systems depend on high quality input. Brands that provide rich, clean and comprehensive data will be better placed to emerge from AI-generated responses.

Third, measurement models will change. As AI mediates discovery, interpretation becomes more difficult. Expect more reliance on AI-driven modeling and performance reporting.

The big question: Who owns the adoption?

If AI assistants become the first place to research and buy, the user interface itself becomes the most valuable part of marketing. OpenAI and Google are both positioning themselves as that interface – but with different economic models.

Google has decades of advertising infrastructure and revenue dependencies. OpenAI is new in the space and must balance monetization and maintaining loyalty to an assistant that many users see as neutral.

For marketers, the takeaway is not to pick sides yet. It is a preparation for both.

• Prepare structured data.
• Invest in original, authoritative content.
• Design art that can work within AI-generated briefs.

Also monitor how labeling, placement and targeting appear in the discussion area.

The time for ten green links is fading. The era of AI-mediated adoption is accelerating. And both Google and OpenAI want to own the ad layer inside it.