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AI search is changing how people discover and compare brands, but it has not made Google or digital marketing obsolete. Marketers are adding channels such as print, direct mail, events, podcasts, catalogs, and newsletters because those can earn sustained attention and create direct relationships—while they continue improving visibility in AI answers and measuring whether any channel contributes to business results.
Is AI search replacing Google?
No. The available evidence points to changing search behavior, not a wholesale move away from traditional search. In a Gartner survey of 365 U.S. consumers conducted in July and August 2025, 51% said their research habits had changed because of generative AI. Gartner also reported that consumers continued to rely heavily on Google and social platforms, and that more than two-thirds continued past Google’s AI Overview.
A separate Gartner survey of 377 U.S. consumers, conducted in June and July 2025, found mixed effects: 31% said they spent more time searching because of AI summaries, while 16% spent less. For purchases, 31% said they considered more options because of AI Overviews, while 7% considered fewer. AI summaries can change the path people take without ending their research.
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Traffic claims also depend on which measure and publisher you use. Google said its total organic click volume was “relatively stable year-over-year” and that it sent “slightly more quality clicks,” describing its own observations rather than publishing a percentage change. Google defines a quality click by whether users avoid quickly clicking back. Other reports cited by WP Engine describe fewer click-generating searches and fewer clicks when an AI summary appears. Those claims are not a single universal traffic figure; they reflect different measures and sources. Google’s account of its search traffic observations and WP Engine’s discussion of marketers’ channel shifts should be read with that distinction in mind.
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Why are marketers bringing back direct mail and print?
AI answers can influence discovery and comparison inside an interface, sometimes without sending someone to a brand’s website. Print, direct mail, live events, podcasts, physical catalogs, and newsletters offer different ways to earn attention and build a relationship beyond a search result. The point is not that these channels are inherently more effective; it is that a marketing mix need not depend on a single discovery route.
Jacqueline Loch, executive vice president of strategy and revenue at AZURE Media, described the standard for these channels in a Content Marketing Institute interview quoted by WP Engine: “Earn attention and be worthy of your customer’s time by making print worth keeping, newsletters worth opening, events worth attending.” A channel earns a place in the mix when its experience is useful or distinctive enough to merit the audience’s time.
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These formats also differ in what they can show a marketer. A search referral can be observed as a visit; a newsletter may build repeat attention; an event creates an in-person interaction. None automatically proves revenue impact, and direct mail or print should not be treated as a cure for weak digital reach. Compare channels against the outcome they are meant to deliver—discovery, attention, engagement, or conversion—rather than assuming that their formats make them successful.
How can brands get found in AI search?
AI answers draw on a broad and variable set of sources, not only a brand’s own website. McKinsey’s 2025 analysis reported that, in many cases, brand-owned sites accounted for 5–10% of sources referenced in AI search. It said source mix varies by model, location, category, and question, and identified affiliates and user-generated content among relevant source types. That makes credible third-party information and community discussion relevant alongside clear, useful owned content.
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McKinsey’s August 2025 AI Discovery Survey, which included 1,927 respondents, found that 44% of AI-powered search users named it as their primary and preferred source of insight. In the same survey, 31% named traditional search, 9% retailer or brand websites, and 6% review sites. These are survey responses about preferred insight sources, not a forecast that those channels will capture the same share of purchases in every category or market. McKinsey’s analysis of discovery in AI search provides the survey context and its qualifications.
For marketers, the practical response is to make brand information accurate and useful wherever prospective customers may encounter it:
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- Keep owned pages clear, current, and specific enough to answer real customer questions.
- Pay attention to credible third-party and community sources that influence how a brand or category is described.
- Check AI answers for both presence and accuracy; being mentioned is not useful if the description is wrong or the context is unfavorable.
- Keep working on conventional search visibility, since AI answers and traditional search are part of an overlapping discovery mix.
Are AI search visitors worth more?
The evidence here does not establish that AI-referred visitors convert at a higher rate or produce more revenue than visitors from traditional search. Nor does an AI answer mention, by itself, demonstrate commercial impact. Treat the value of AI visibility as a question to measure for your own audience and business, not as a settled industry-wide result.
Semrush’s 2026 article reporting its marketer survey illustrates the measurement gap: 49% of respondents said measuring AI’s impact on pipeline or revenue was a top challenge, and 45% said measuring visibility in AI answers was difficult. Those are survey findings, not audited measures of all marketing teams. Semrush also reported that 85% said AI had changed their search strategy, while 22% said SEO and AI search were fully integrated across strategy, execution, and reporting.
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What should marketers measure if fewer people click?
Do not force unlike signals into one number. A click, an engaged visit, an appearance in an AI answer, and a closed sale describe different stages and should be tracked separately before they are connected to outcomes.
- Organic referrals: Track conventional search clicks and visits as their own measure. Changes in click volume can matter even when other forms of visibility rise.
- Engaged visits: Look beyond the arrival to whether a visitor stays, explores, or takes a useful next step. Google’s “quality click” description concerns users not quickly clicking back; it is Google’s definition, not a universal engagement standard.
- AI-answer presence and accuracy: Record whether the brand appears in relevant answers and whether those answers represent its products or expertise correctly.
- Cross-channel attention: Measure the response appropriate to the channel, such as newsletter engagement or event participation, rather than treating every exposure as a website referral.
- Pipeline and revenue: Connect channel observations to downstream outcomes where attribution permits, while acknowledging that measurement may not isolate a single channel’s contribution.
Semrush reported that 38% of surveyed marketers planned investment in AI search optimization and 25% planned spending on AI visibility tools. That indicates interest in the category among its respondents, not proof that a tool or tactic will produce returns. The broader gap is organizational: strategic awareness is more common in the survey than full integration across execution and reporting. Semrush’s marketer survey findings describe the reported challenges and planned investments.
Quick Recap
How should a marketing team respond?
- Keep traditional search in the plan. Gartner’s consumer findings and Google’s account do not support treating AI as a complete substitute for search engines or web referrals.
- Audit discovery paths. Identify where customers encounter the brand: search results, AI answers, third-party sources, communities, newsletters, events, and other relevant channels.
- Choose channels for a reason. Use print, direct mail, podcasts, events, catalogs, or newsletters when they can deliver a distinctive, useful experience to the audience—not merely because they are old formats.
- Assign separate measures. Track referral clicks, engaged visits, AI-answer presence and accuracy, channel attention, and downstream pipeline or revenue as distinct signals.
- Review what the evidence says locally. Compare channel performance for your own audience, geography, category, and goals before shifting substantial resources. The cited sources do not prove that old-school tactics outperform AI search, or the reverse.
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