AI is rapidly reshaping how consumers search and how brands must position themselves across the entire discovery journey. Search is no longer limited to a traditional results page: it has become conversational, multimodal and fragmented across platforms. Consumers move between Google, TikTok, Reddit, Amazon, ChatGPT, Copilot and Perplexity, often without ever clicking through to a website. With zero-click interactions rising and AI-generated summaries becoming common in complex queries, brands are increasingly discovered inside these experiences rather than through traditional search listings.
Search behaviour and technological advancements impact ad formats
This shift is reinforced by behavioural changes. Users now ask full questions, refine them in multiple steps and mix text, voice and visual queries. Google Lens processes billions of monthly searches, and more than 30% of users employ voice search. Younger audiences accelerate the trend: TikTok has become the preferred search destination for Gen Z, and forums such as Reddit have gained relevance thanks to their perceived authenticity and deeper integration into AI training models. Meanwhile, AI tools such as ChatGPT and Perplexity are emerging as alternative discovery engines, influencing early research even if they still generate less raw
traffic than Google. If you know that Perplexity already has ads running in the USA and OpenAI is working hard on ad formats within ChatGPT, we can expect a lot more different opportunities for advertisers very soon.
From keywords to intent with a multimodal approach
This new landscape also affects how paid search functions. Ads are no longer limited to fixed slots on a results page. In AI Overviews and chat-based interfaces like AI Mode or Copilot, ads can appear above, below or directly inside generated answers. They are selected based on meaning and context rather than exact keyword matches and increasingly incorporate multimodal elements such as images, video snippets or product cards. As these environments grow, brands must shift from keyword-based optimisation to intent-driven, structured and adaptable content.
How advertisers can change their search strategy to be future-proof
To navigate this transition, five practical levers help advertisers guide the machine.
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Speak the language of intent: Write ads and landing pages in natural, human
phrasing. Use questions, comparisons and clear benefit statements that align with how users speak in conversational search.
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Design for dialogue: Treat discovery as an evolving conversation. Ads should behave like helpful answers and support follow-up queries such as budget filters or product attributes.
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Build modular, AI-ready assets: AI assembles ads from small components—headlines, visuals, features, reviews. Provide structured, diverse assets and maintain consistent product data across platforms.
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Strengthen first-party data: High-quality CRM signals, offline conversions and value-based outcomes train algorithms to optimise toward real customers, not superficial metrics.
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Embrace automation with control: Let AI generate variations and test combinations, but establish clear brand guardrails, goals and experiment frameworks.
Conclusion with two guiding principles
Two guiding principles remain essential.
Stay critical: new features evolve quickly, and early tests can deliver mixed results, especially regarding conversion quality.
And monitor closely: AI may chase volume or low-cost clicks unless business-oriented signals are clearly defined. AI is changing where, how and when people search and paid search is evolving with it. By preparing assets, data and creative structures for an AI-driven environment, brands can remain discoverable in a landscape where answers matter as much as clicks.
Jonas Geiregat
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