LLM-Powered Search vs. Traditional Search: 2025

For decades, search meant Google. You typed a query, got a list of blue links, and clicked through to find an answer. That model still commands the majority of global search traffic. But for the first time in over a decade, its grip is loosening.

LLM-powered assistants — ChatGPT, Perplexity, Gemini, Claude — are handling a growing share of the questions that used to go to Google. Not because people are abandoning traditional search, but because the total amount of search activity is growing and AI is absorbing most of that new demand. By 2030, the consensus across industry forecasts is that AI-powered platforms will handle more than half of all global search queries.

This piece lays out what we know about the current state of the shift, where it is heading year by year through 2030, and what it means in practice for brands that want to stay visible as the discovery landscape changes.

1. Where things stand in 2025

Google still dominates. It processes roughly 15 billion searches per day, holds approximately 90% of global search market share, and saw over 20% year-on-year growth in 2024 — driven partly by its own AI features. Traditional search is not in decline. It is still growing.

What has changed is who is growing faster. ChatGPT reached 100 million users in two months after launch, the fastest consumer app adoption ever recorded. By early 2025, it was handling approximately 1 billion interactions per day and had surpassed Bing's web traffic. Among US adults, 52% have now used an AI assistant, and two-thirds of those users report using it like a search engine.

LLM-based search currently accounts for around 5.6% of US desktop search traffic (Wall Street Journal, June 2025) — up from roughly half that figure a year earlier. In absolute terms this is still a small share. In trend terms, it is one of the fastest-growing segments in the history of consumer technology.

The important framing: this is not a zero-sum shift. Global search-related sessions grew 26% worldwide between Q1 2023 and Q4 2025. AI is adding to the total, not simply redistributing it.

2. How users are dividing their searches

98% of ChatGPT users still also use Google. They are not replacing one with the other — they are allocating different types of queries to different tools.

The pattern that is emerging is fairly consistent across studies:

Google for quick facts, navigational queries, local search, and transactional intent.
AI assistants for complex research, multi-step reasoning, planning, comparisons, and anything that would previously require reading multiple pages.

This division of labor is already showing up in category-level data. In sectors like programming, academic research, and detailed product recommendations, AI-first platforms are already capturing over 60% of queries. The crossover in these high-complexity verticals is not forecast for 2028 — it has already happened.

Younger users are accelerating the overall shift. Nearly 80% of Gen Z have used generative AI tools, with close to half using them weekly. For this cohort, reaching for an AI assistant first is already the default for information-seeking tasks.

3. How Google and Microsoft are responding

Neither Google nor Microsoft is conceding the search market. Both are deploying significant capital to integrate LLMs into their core search products.

Google launched its AI Overviews (formerly SGE) in 2024 and is investing $75 billion in AI infrastructure. CEO Sundar Pichai called 2025 “critical” for the company’s AI response. Google’s head of search has acknowledged that the traditional search bar will become less central over time as AI interfaces take over — essentially, Google is rebuilding itself from inside.

Microsoft integrated ChatGPT into Bing via its $13 billion+ OpenAI partnership. Within a month of launch, Bing exceeded 100 million daily active users for the first time. Around a third of Bing's daily users now engage with its AI chat feature.

The direction from both incumbents is the same: the future of search is AI-first. The question is whether users stay inside Google's ecosystem for that AI experience, or whether they migrate to independent platforms like ChatGPT and Perplexity.

4. The year-by-year forecast: 2025–2030

Here is what the data and leading analyst projections suggest for each year of the transition.

Year	What to expect
2025	LLM queries represent less than 5% of global search volume, but ChatGPT crosses 1 billion weekly searches and 800 million weekly active users. Over a third of consumers use an AI assistant daily or near-daily. AI search is mainstream in awareness; not yet mainstream in volume.
2026	Gartner projects traditional search engine volume drops 25% as users shift toward generative AI for research and discovery. Google's query count could begin declining from its peak of ~14 billion/day. A quarter of all search queries may be handled by AI platforms. Apple's potential entry into AI search adds another major distribution vector.
2027	AI-driven traffic begins to demonstrate higher economic value per visit. Ahrefs data shows AI search visitors converting at up to 23× the rate of organic search visitors; Semrush puts the average at 4.4× higher. Specific verticals — coding, healthcare, financial research — see AI platforms surpass Google in query share. The business case for GEO investment becomes hard to argue against.
2028	Gartner's forecast: organic search traffic to websites is down 50% or more. Semrush projects AI-powered search could overtake traditional search traffic in the first half of 2028. AI-first search engines are estimated to handle 30–40% of all informational queries across industries. Google's SGE likely becomes the default search mode for most users.
2029–2030	LLM-powered platforms collectively command over 50% of global search query volume. Kevin Indig's modeling (based on Similarweb traffic trends) projects ChatGPT's traffic will surpass Google's around October 2030. The line between "AI assistant" and "search engine" dissolves — most users will not make the distinction.

The consensus across Gartner, Semrush, and independent analysts converges on the same window: 2028–2030 as the period when AI-driven search becomes the dominant mode of information discovery globally.

5. What will speed up - or slow down - the transition

The timeline is not fixed. Several factors will determine whether the crossover comes closer to 2028 or to 2031.

Accelerants

Accuracy and trust: As LLMs improve at citing reliable sources and handling real-time queries, users have less reason to double-check on Google. Trust is already at roughly 70% for AI-generated answers among regular users.
Ambient integration: Microsoft is embedding ChatGPT across Windows and Office. Apple is integrating AI into iOS. When asking a question yields an immediate AI answer without opening a browser, the search bar becomes optional.
Voice and multimodal search: 8.4 billion voice assistants are in use globally as of 2025. As these integrate advanced LLMs, conversational AI search becomes the natural interface for on-the-go queries — a mode where traditional search cannot compete.

Constraints

Content ecosystem risk: 60% of Google searches already end with no click. If publishers restrict content access or regulators intervene to protect click-through economics, AI search growth could slow. Equally, if monetization models for AI-native advertising are established, the reverse is true.
Google's own transformation: If Google successfully retains users through its own AI search product, the "AI overtakes Google" narrative may never materialize as a clear moment — instead, Google itself becomes the AI search platform. The tipping point arrives inside Google, not against it.

6. What this means for brand visibility

The shift from traditional search to AI-powered discovery changes the rules of visibility in one fundamental way: ranking is no longer the primary objective. Being cited is.

In traditional search, you optimized to appear in the top 10 results. In AI search, the model synthesizes an answer and either mentions your brand or it does not. There is no position two or three — there is mentioned, or not mentioned.

Several patterns from current data are worth anchoring on:

Brand mentions correlate 3× more strongly with AI citations than backlinks (Ahrefs, December 2025 study of 75,000 brands). YouTube mentions show the strongest individual correlation at 0.737.
Only 11% of domains are cited by both ChatGPT and Google AI Overviews for the same query. Optimizing for one platform does not automatically translate to the other.
92% of AI Overview citations come from top-10 ranking pages, but 47% come from pages below position 5 — different selection logic than traditional search. High-quality, structured content can surface in AI answers even without top-three organic rankings.
Multi-modal content — text, images, and structured data together — sees 156% higher selection rates for AI citations (GEO research, 2025).

The practical implication: SEO strategy needs to extend into GEO. This does not mean abandoning keyword rankings. It means building content that AI models can parse, cite, and trust — and then tracking whether they actually do.

Kime tracks brand visibility across ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude, and DeepSeek. It shows where your brand is being cited, where competitors are appearing instead, and which actions will move the needle — scored by predicted impact, not just listed as suggestions.

7. What to do now

The crossover is not going to announce itself. By the time AI-powered search overtakes traditional search in your category, the brands that started building AI visibility two years earlier will have a compounding advantage. Kime's data consistently shows brands that have structured, well-cited content across AI platforms already outperforming those relying on SEO rankings alone.

Three concrete starting points:

Audit your AI presence today. Run your key category prompts across ChatGPT, Perplexity, and Google AI Overviews. If your brand is not appearing in answers to the questions your customers are asking, you have a visibility gap that SEO rankings will not fix.
Structure content for citation. AI models prefer citing passages of 134–167 words written as self-contained answer blocks. Content with structured data and server-side rendering gets indexed; JavaScript-only pages are invisible to AI crawlers entirely.
Measure share of voice, not just rankings. The equivalent of a keyword ranking report in AI search is a visibility score across platforms — how often your brand appears, in what context, with what sentiment, relative to competitors. Track this weekly so you can see movement before it shows up in traffic.

The bottom line

The question of when AI search overtakes traditional search is becoming less relevant than the question of whether your brand will be visible when it does. The crossover is projected between 2028 and 2030. That is two to four years. It is enough time to build a meaningful advantage — and not enough time to wait and see.

The brands that treat AI visibility as a primary channel today are building the kind of compounding advantage that will be very difficult to close in 2028. The ones that wait for the crossover to be undeniable will be starting from zero when it matters most.

FAQ

Q1: Will ChatGPT replace Google by 2030?

Complete replacement is unlikely. The more accurate picture is a hybrid model — AI assistants handle most complex, research-oriented, and conversational queries, while traditional search remains relevant for navigational, local, and transactional searches. Within Google itself, the AI-first mode is likely to be the default by 2028. The "Google vs. AI" framing may resolve itself by Google becoming the AI search platform, not losing to it.

Q2: How does AI search change SEO?

The goal shifts from ranking for keywords to being cited as a trusted source in AI-generated answers. This means building content that is authoritative, well-structured, and easy for AI models to parse and reference. Brand mentions, structured data, and server-side rendering matter more. Backlinks matter less. Tracking 'share of voice' in AI responses replaces tracking keyword positions as the primary visibility metric.

Q3: Which industries will be affected first?

The sectors where AI-first search dominance is already measurable are programming and developer tooling, academic research, complex product comparison, healthcare information, and financial planning. These are all high-complexity, research-intensive query types where conversational AI adds the most value over a list of links. Consumer categories with high-volume, low-complexity queries will take longer to shift.

Q4: How do I track my brand's AI visibility?

The starting point is running your category's most important prompts across major AI platforms — ChatGPT, Perplexity, Google AI Overviews, Gemini — and recording whether your brand appears, in what position, and with what sentiment. At scale, this requires automation. Kime runs daily tracking across six LLM platforms, groups results by topic category to smooth non-deterministic variation, and benchmarks your performance against named competitors.

Sources: SparkToro 2024 search volume research; Gartner AI adoption forecasts; Kevin Indig industry analysis (Similarweb data); OpenAI usage statistics; Wall Street Journal June 2025; Ahrefs December 2025 (75,000 brand study); Semrush GEO research 2025.