Generative AI Statistics: The Latest Trends & Insights

2025 marked a clear turning point for generative AI. The year the technology moved decisively from early-adopter novelty to everyday utility. It now shapes how we search, learn, create, and make decisions online. 

The sudden increase in traffic is just the tip of the iceberg. What’s even more interesting is who is using AI, and how. 

Once dominated by younger digital natives, the audience is rapidly broadening. Users aged 18–34 still form the largest share, but their share has dropped from 61% to 53%, as older demographics increasingly incorporate AI tools into their daily workflows. 

As detailed in Similarweb’s 2025 Generative AI Landscape report, the shift is unmistakable. Generative AI has moved from a curiosity used by early adopters to a daily tool shaping decisions, discovery, and behavior across the web.

Gen AI stats: How AI overtook the web

1. What the latest Gen AI adoption data reveals

• Gen AI platforms now receive 7 billion average monthly web visits, which is a 76% increase year over year
• Gen AI app downloads have reached 1.9 billion, up 319% from the previous year
• 53% of Gen AI users are between the ages of 18 and 34
• Referral traffic from Gen AI platforms has climbed to 2 billion visits, which is a 778% year-over-year increase
• 7% of Gen AI traffic goes to transactional sites, two percentage points higher than Google

Generative AI adoption has accelerated at a pace few technologies have matched. Over the past year, monthly web visits to Gen AI platforms climbed to 7 billion, while mobile apps surged with 1.9 billion downloads, signalling a shift from experimentation to habitual, everyday use. 

	Google	YouTube	Facebook	Instagram	ChatGPT	Amazon	X/Twitter	Reddit	Whatsapp	Wikipedia
June 25	1	2	3	4	6	6	7	9	8	9
July 25	1	2	3	4	5	5	7	8	9	11
August 25	1	2	3	4	6	6	7	8	9	11
Sept 25	1	2	3	4	6	6	7	8	9	10

The data above, showing the top 10 websites by monthly visits for June 2025 to September 2025, demonstrates how ChatGPT, which now commands nearly 80% of global Gen AI traffic, has risen into the world’s top five websites. 

This underscores its dominance even as platforms like Gemini, Perplexity, and Claude carve out fast-growing niches. Together, these trends reveal a maturing landscape defined by rapid adoption, clear category leaders, and an increasingly competitive ecosystem.

2. Competitive landscape stats

The Gen AI landscape data, demonstrates that the AI landscape is entering a new era defined by both clear leadership and growing fragmentation. At the top of the hierarchy sits ChatGPT, which accounts for nearly 80% of global Gen AI visits.

	ChatGPT	Gemini	Deepseek	Grok	Perplexity	Claude	Copilot
April 25	5843.1	411.4	480.1	196.1	113.1	95.6	89.8
May 25	6135.0	529.5	436.2	178.6	126.8	99.7	92.4
June 25	6042.1	650.2	385.8	158.3	129.5	113.3	83.6
July 25	6340.3	701.1	350.5	201.5	140.6	125.2	93.6
Aug 25	6393.9	724.6	319.3	190.9	148.2	148.5	95.9
Sept 25	6319.9	1058.9	333.0	176.7	169.5	157.0	99.6

But beneath this dominance, the market is diversifying quickly. Google’s Gemini is gaining momentum through tight integration with Search and Workspace, while emerging players are carving out niche audiences seeking advanced reasoning, open-source transparency, or privacy-focused alternatives. 

3. How users move between web and mobile AI

As generative AI becomes part of everyday digital behavior, users are increasingly moving fluidly between web and mobile, but mobile is where the deepest engagement is taking shape. This signals a shift from casual exploration to embedded, habitual use.

	MAU	Stickiness
ChatGPT	41.3	33%
Perplexity	3.4	17%
Copilot	3.1	14%
Gemini	2.4	5%
Grok	1.8	14%
Claude	1.3	16%
Deepseek	0.8	12%

Within mobile, AI apps are beginning to split into two clear tiers: 

• Scale platforms
• Specialised tools

AI Apps data measuring monthly active users and stickiness for October 2024 to September 2024 shows that ChatGPT dominates with 41 million monthly active users and a 33% stickiness rate, far outpacing other competitors, which is a sign that it has become a daily-use utility for millions. Meanwhile, AI apps bring smaller audiences and much lower stickiness rates (5%–17%), reflecting more occasional, task-specific use.

Together, these shifts illustrate a maturing ecosystem. The web drives reach, mobile drives routine, and users are increasingly gravitating toward platforms that offer both breadth and depth, or niche tools that deliver targeted value.

Gen AI session stats

1. Shifting intent behind AI prompts

Below we see Google search intent based on keyword categorization for October 2024 to September 2024.

	Google Search
Informational	63.8%
Navigational	25.2%
Transactional	8.7%
Other	2.3%

ChatGPT prompt intent categorized by OpenAI from May 2024 to June 2025.

	ChatGPT Prompt Intent
Seeking Information	19.2%
Purchasable Products	2.1%
Writing & Creative Ideation	32.0%
Practical Guidance	24.4%
Technical & Other	22.4%

Gen AI sessions reveal a fundamentally different pattern of user intent compared to traditional search. 

While Google searches remain heavily informational (64%), ChatGPT interactions are far more varied, with only one in five prompts focused on information retrieval. 

Instead, users turn to AI for creative ideation (32%), practical guidance (24%), and a growing set of technical or problem-solving tasks (22%).

	avg_length_words
Google	3.4
AI Mode	10.4
ChatGPT	60.0

This shift also shows up in how people engage. The query length data above shows that ChatGPT prompts average 60 words, with informational search queries averaging 31.2 words, compared to Google’s 3.4-word queries, reflecting a move toward richer, more contextual inputs designed to shape personalized responses. 

As a result, Gen AI sessions are becoming more conversational, iterative, and exploratory, blending search, creation, and decision-making into a single flow. 

2. Where Gen AI sources its answers 

The nature of AI-generated citations is evolving. ChatGPT continues to increase the share of responses that reference external sources, drawing heavily from publishers, review sites, and platforms like Reddit. 

This creates a discovery ecosystem where brand influence depends not just on owned content, but on how frequently a brand is referenced in the broader web, from expert reviews to community discussions.

Below, we see the share of citations by category comparing ChatGPT and AI Mode for September 2025, analyzing the top 10K citations.

	News & Publishers	Reviews & UGC	Business Services	Social Media	Ecommerce Brands	Marketplace	Consumer Services	Financial Services	Search & Discovery
ChatGPT	36.9%	18.9%	11.4%	8.7%	7.8%	7.3%	4.9%	3.3%	0.7%
AI Mode	34.5%	26.9%	5.3%	13.5%	6.2%	4.1%	7.0%	1.4%	1.0%

3. Outgoing AI traffic stats: Traffic begins to level out

Below, we compare growth in referrals to referrals per visit from October 2024 to September 2025. 

	Referrals	Referrals Per Visit
Oct 24	73.4M	0.12
Nov 24	108.9M	0.17
Dec 24	109.9M	0.18
Jan 25	118.0M	0.18
Feb 25	135.0M	0.17
March 25	149.4M	0.17
April 25	183.4M	0.19
May 25	211.3M	0.21
June 25	219.5M	0.22
July 25	239.4M	0.22
Aug 25	224.5M	0.20
Sept 25	233.7M	0.2

 

Referral behavior highlights another major shift. While overall referral volume from Gen AI platforms grew sharply earlier in the year, the referral data above demonstrates that it’s begun to plateau, and referral rates remain modest. Google Search drives referral rates of 17–19%, whereas Google’s AI Mode averages just ~2%, and ChatGPT sends relatively few outbound clicks.

• Users referred from ChatGPT spend an average of 15 minutes on site, compared with 8 minutes for Google referrals.
• ChatGPT referrals generate an average of 12 pageviews per visit, versus 9 from Google.
• The conversion rate from ChatGPT referrals to transactional sites is 7%, compared with 5% from Google.

Yet when users do click through from AI platforms, their visits are significantly higher quality: longer time on site, more pageviews, and stronger conversion rates than traditional search traffic.

4. How new AI engines are changing discovery

Below, we see the number of active users on AI Mode in the first two months amongst AI Mode users from May 20th to July 19th.

	US	UK
1 Day	56.4%	52.9%
2 Days	20.5%	21.0%
3 Days	9.6%	10.3%
4 Days	5.1%	5.6%
5+ Days	8.4%	10.3%

Discovery is rapidly evolving as generative AI becomes a central gateway to information. One major shift is the rise of AI-powered interfaces embedded directly into users’ existing digital habits. Google’s AI Mode, the fastest Gen AI platform to reach 100M US visits, blends conversational answers with traditional search, indicating a future where discovery happens inside hybrid environments rather than across standalone tools.

	chatgpt.com/atlas	perplexity.com/comet
19 Oct		21956
20 Oct		26737
21 Oct	180774	30315
22 Oct	142626	23953
23 Oct	72794	24378
24 Oct	40896	19845
25 Oct	15361	14325
26 Oct	20183	14371
27 Oct	15821	13954
28 Oct	17437	13121
29 Oct	49982	12680
30 Oct	46552	12802
31 Oct	33318	8382
01 Nov	27268	9641

At the same time, the data shows that AI browsers are redefining how people interact with the web, allowing users to query, analyze, and act on what appears on their screen in real time. Early adoption spikes suggest that browsing itself is becoming an AI-driven experience.

AI is also redefining how brands appear in discovery pathways. LLMs increasingly favor  news publishers, authoritative content, and user-generated platforms like Reddit, often surfacing deep, niche pages rather than top-level URLs. The result is that visibility is being won by focusing on off-page strategies.

The new AI search playbook

1. What brand visibility looks like in AI search

Unlike search engines that send users directly to external sites, Gen AI platforms synthesise information and surface brands only when they appear as trusted, repeated signals across the web. This new dynamic makes visibility, not traffic, the defining KPI for AI-era discoverability.

Brands with well-structured, authoritative, and frequently referenced content rise to the top of AI conversations. In retail, for example, leaders like Target and Walmart appear in more than half of relevant AI responses, while in travel, established platforms dominate brand mentions. These patterns reveal how AI models prioritize brands that consistently appear across reputable sources, UGC platforms, and deep content pages.

2. Structuring content for AI discovery

Content structure and depth have become crucial for being surfaced in Gen AI answers. Unlike traditional search engines that favor top-level, keyword-optimized pages, LLMs pull heavily from deep, highly specific URLs, with a third of ChatGPT citations coming from pages three folders deep and significant volume from even deeper paths. 

This means brands must prioritize detailed, intent-rich content that answers precise user questions, especially long-tail, conversational prompts that LLMs excel at interpreting.

Clarity and structure matter just as much as depth. AI models more easily interpret pages with:

• Clearly labelled sections
• Bullet-point summaries
• Distinct product or feature attributes

The report highlights how Walmart’s product detail pages, with a dedicated “About this item” section, outperform less-structured competitors like Temu in AI visibility. Well-organised content creates a reliable blueprint for LLMs to extract and synthesise information.

But being the source isn’t the only path. LLMs also favor citing authoritative third-party domains, including publishers, expert reviews, and user-generated platforms such as Reddit. To fully optimize for AI visibility, brands must analyze their citation share and ensure not only that their own content is structured for machine understanding but also that they appear across the ecosystem of sources AI trusts.

In the AI era, content optimization expands beyond SEO. It’s about creating information that is machine-readable, deeply specific, and repeatedly validated across the web, the signals LLMs use to decide which brands deserve to be part of the answer.

3. Signals shaping the future of Gen AI

The next wave of AI-driven discovery is already taking shape, and several clear signals point to where the landscape is heading. First, AI is becoming embedded in everyday browsing, with Google’s AI Mode reaching 100M U.S. visits faster than any Gen AI platform and shifting discovery into hybrid search–AI interfaces. At the same time, AI-native browsers like ChatGPT Atlas, and Perplexity Comet are redefining how users interact with the web, turning the browser itself into an intelligent assistant.

Another key shift is the volatility of AI citations. Changes such as Google’s September algorithm update caused a sharp drop in Reddit citations, illustrating how quickly AI retrieval patterns can shift, and how directly they can affect brand visibility.

Finally, LLMs continue to prioritize deep, authoritative, and niche content, as well as trusted external sources like publishers and UGC platforms. Brands that invest in long-tail content and credible off-site signals will be best positioned as AI systems become more selective in what they surface.

Here is what one SEO market leader is saying:

“Generic, educational content no longer works for brands attempting to win on LLMs. Generative engines have completely eliminated the top of the funnel, as they simply provide the answers to queries without sending any referral traffic.

Truly winning on AI search demands tactical, bottom-of-the-funnel, niche content that answers the user’s query in the shortest amount of time in the most tactical way.

This is exactly why original data and building brand authority have become the two most important factors for SEO and GEO.

With so much content being produced at scale, generative engines have no other choice, than to refer traffic to the most authoritative source.” – Austin Heaton, SEO Consultant

Winning the next phase of AI discovery

Generative AI has already rewritten the pathways of online discovery, and its influence is accelerating. User behavior is shifting, platforms are fragmenting, and visibility is being reshaped in real time. In a landscape this fluid, gut instinct isn’t enough. Brands need a data-driven understanding of where they stand, how they’re being surfaced in AI answers, and what signals engines are responding to. The winners will be the ones who track these shifts early and use real insight to stay ahead of the next wave.

FAQs

How is generative AI changing the way people search online?

Generative AI shifts discovery from keyword lookups to conversational queries, synthesised answers, and deeper intent-driven interactions. This changes not just how people search but where decisions are made.

Why are citations becoming more important in AI answers?

Because LLMs increasingly rely on live web data. Citations reveal which sources AI trusts, and which domains are shaping AI’s recommendations.

What makes AI-driven referral traffic different from search traffic?

AI referrals are smaller in volume but significantly higher in intent. Users who click through tend to spend more time on-site and convert at higher rates.

How can marketers measure success in the AI era?

Traditional rankings matter less. New key metrics include visibility in AI responses, citation frequency, sentiment in recommendations, and off-site influence.

Why is ongoing data essential for competing in AI search?

Because AI models update frequently, citation patterns shift, and platform behaviour changes rapidly. Up-to-date data is the only way to understand where you’re gaining (or losing) visibility in real time.