How to Scrape Google AI Mode in 2025

With the launch of Google AI Mode, search results now come with AI-generated summaries that pull together insights from multiple sources. Instead of scanning endless links, users can get direct, conversational answers and even follow up with new questions in natural language.

For businesses, researchers, and developers, this isn’t just a user-friendly upgrade – it’s a brand-new layer of valuable data. Scraping AI Mode (and combining it with other Google targets) opens the door to a competitive edge. Let’s explore what AI Mode is, why it matters, and how you can take advantage of its key features.

What is Google AI Mode?

Google AI Mode is the search engine’s new way of answering questions with conversational responses at the top of results page. Instead of just a list of links, users see a direct AI-generated summary that feels more like a dialogue. From there, they can click into cited sources or even ask follow-up questions naturally, as if they were chatting with an assistant.

It’s worth noting that Google AI Mode is not yet available in every country. Access is being rolled out gradually, so some regions may not see these conversational responses in their search results yet.

Behind the scenes, AI Mode isn’t just one search query – it uses a process sometimes called “query fan-out.” This means that when you ask a question, Google breaks it down into smaller pieces, runs multiple searches in parallel, and then stitches together the most relevant information. The result is a richer, more context-aware response than traditional search results alone.

At its core, Google's AI Mode is powered by Gemini, Google’s large-scale AI model, which works alongside existing search systems. This combination allows AI Mode to go beyond matching words on a page – it can synthesize information across multiple sources, highlight key takeaways, and present them in a way that’s both concise and useful.

For everyday users, this makes searching feel faster and more intuitive. But for businesses and data-driven professionals, it also represents a new layer of dynamic content that can be scraped, analyzed, and applied to everything from market research to content strategy.

Google AI Mode vs Google AI Overviews

While these two sound similar, Google AI Mode and Google AI Overview differ quite a lot. 

Google's AI Overview is the concise, AI-generated summary at the top of standard search results. It offers quick answers to complex or informational queries, allowing users to get the information they need without navigating through multiple pages. Google AI Overview results are seamlessly integrated into the standard search experience, rather than a separate interface.

In contrast, Google AI Mode is a dedicated, conversational search experience that transforms the entire interface. It allows for multi-step, interactive queries and more in-depth, context-aware interactions similar to a chatbot. AI Mode is a separate, more comprehensive environment designed for deeper exploration – it provides information from multiple web sources and suggests follow up questions based on the search queries by other human users.

Why scrape Google AI Mode data?

Unlike classic search results, which simply list pages, AI Mode condenses multiple perspectives into a single, conversational summary. That makes it a unique structured data source for anyone who needs to understand not only what information is out there, but also how it’s being interpreted and prioritized.

For businesses, this means real-time intelligence. A company can monitor how its brand, products, or competitors are being described by Google’s AI, and track shifts in messaging over time. For marketers, it’s a direct window into customer intent: the follow-up questions AI Mode suggests often reflect exactly what people are curious about next.

Scraping AI Mode also saves effort. Instead of gathering and analyzing hundreds of raw search results, you get a pre-processed synthesis – effectively, Google has already done the heavy lifting of sorting, clustering, and summarizing. That means faster insights with less data cleaning.

And because every AI Mode summary comes with citations, you’re not just scraping opinions in a vacuum. You can capture the underlying sources, building richer datasets for competitive research, content strategy, SEO optimization, or competitive analysis.

In short, Google AI Mode is more than a convenience for searchers – it’s a valuable signal for anyone who relies on high-quality, structured information. Scraping it gives you both the map and the territory.

How to scrape Google AI Mode with Web Scraper API

Scraping Google AI Mode conversations doesn’t have to be complicated. With Web Scraper API, the process is simple, and you can use the programming language you’re most comfortable with. Here, you will see a Python step by step guide to get reliable results.

1. Install dependencies

Let’s start by setting up a Python virtual environment and installing the requests library.

pip install requests

2. Configure API parameters

Next, create a new Python file and import the json and requests modules. We’ll use these to send HTTP requests to the API and save the response as a JSON file.

Within the created file, we’ll begin assembling a request for the Web Scraper API. The payload dictionary will hold the required parameters that the API supports. In our case, we have to specify the source and the query.

• Source tells the API what type of scraper to use. Here we’ll set it to google_ai_mode.

• Query is where you provide the text of your AI request (e.g., a search question or task for the model).

For this case scraping job, enable JavaScript rendering and turn on automatic parsing. Instead of doing tedious manual scraping, the platform handles all the heavy lifting for you – rendering JavaScript, parsing the output, and returning a structured response.

import json
import requests

payload = {
    'source': 'google_ai_mode',
    'query': 'high quality and best performance budget laptops',
    'render': 'html',
    'parse': True
}

3. Send a request

After that, send a POST request with your payload to the API endpoint.

response = requests.post(
    'https://realtime.oxylabs.io/v1/queries',
    auth=('USERNAME', 'PASSWORD'),
    json=payload
)

print(response.text)

4. Save results

You can easily save the entire API response in a JSON file, where the scraped and parsed Google AI Mode results are stored in the content object:

with open('response.json', 'w') as file:
    json.dump(response.json(), file, indent=2)

Once the scraper runs, you’ll see a structured response. For clarity, only a trimmed portion is shown here.

{
  "results": [
    {
      "content": {
        "links": [
          {
            "url": "https://www.rtings.com/laptop/reviews/best/at-best-buy#:~:text=It%20feels%20well%2Dbuilt%20even%20though%20it's%20entirely,it's%20relatively%20portable%20for%20a%2016%2Dinch%20device.",
            "text": "The 6 Best Laptops At Best Buy of 2025"
          },
          {
            "url": "https://www.techradar.com/computing/windows-laptops/microsoft-surface-laptop-13-inch#:~:text=Pros:%20+%20Stunning%20design%20+%20Extremely%20portable,MacBook%20Air%20M4%20offers%20far%20better%20performance",
            "text": "Microsoft Surface Laptop 13-inch review: purple imperfect"
          },
          "..."
        ],
        "prompt": "high quality and best performance budget laptops",
        "citations": [
          {
            "url": "https://www.rtings.com/laptop/reviews/best/by-usage/college#:~:text=This%20model%20feels%20well%2Dbuilt%20despite%20its%20low,it's%20relatively%20portable%20for%20a%2016%2Dinch%20device.",
            "text": "Choosing a high-quality, high-performance budget laptop often involves balancing a fast processor and sufficient memory with a sturdy build and reliable display . The following recommendations offer strong performance for common tasks like browsing, productivity, and media consumption, without a high price tag."
          },
          {
            "url": "https://blog.google/products/shopping/shopping-graph-explained/",
            "text": "Choosing a high-quality, high-performance budget laptop often involves balancing a fast processor and sufficient memory with a sturdy build and reliable display . The following recommendations offer strong performance for common tasks like browsing, productivity, and media consumption, without a high price tag."
          },
          "..."
        ],
        "response_text": "Choosing a high-quality, high-performance budget laptop often involves balancing a fast processor and sufficient memory with a sturdy build and reliable display . The following recommendations offer strong performance for common tasks like browsing, productivity, and media consumption, without a high price tag. High-performance budget laptops (under $800) ASUS Vivobook 16 M1605 (2023) The ASUS Vivobook 16 offers exceptional value, packing powerful specs into a budget-friendly package. Performance: Features an AMD Ryzen 7 processor with 16GB of RAM and a 1TB SSD, making it capable of handling demanding multitasking with ease. Display: The 16-inch FHD+ (1920x1200) IPS display is bright and clear, providing a good viewing experience. Design and quality: It feels well-built for a plastic laptop and is relatively lightweight for its size. It also includes a comfortable backlit keyboard and a large, responsive touchpad. Battery: It offers roughly 8 hours of battery life with light usage. Acer Aspire 14 AI (2024) As a \"Copilot+ PC,\" the Acer Aspire 14 AI offers a blend of performance and modern features, including enhanced AI capabilities. Performance: Powered by an Intel Core Ultra 7 processor and 16GB of RAM, this machine can handle creative work and heavy multitasking. Display: Its 14-inch Full HD (1920x1200) IPS display is bright and vibrant, making it a good fit for content creation and media. Design and quality: The aluminum chassis gives it a more premium and durable feel than plastic alternatives. Battery: It has an excellent battery life of up to 14.5 hours under mobile benchmark testing. Asus Vivobook 16 16\" Laptop AMD Ryzen 7 with 16GB Memory $569.99 $649.99 4.6 (1K+) Acer Aspire 14 AI 14\" Laptop Intel Core Ultra 7 256V $1,049.99 4.7 (35) Microsoft Surface Laptop Copilot+ PC (13-inch) The most portable option in this category, the 13-inch Surface Laptop is ideal for users who prioritize mobility and a premium build. Performance: The Snapdragon X Plus chip provides solid performance for productivity and AI-enhanced tasks, though it is not a powerhouse for intensive creative or gaming workloads. Display: The 13-inch touchscreen display is functional but only has a 60Hz refresh rate. Design and quality: As with all Surface products, it boasts a sleek design, excellent build quality, and a top-tier keyboard and trackpad. Battery: Its excellent 23-hour battery life makes it a great choice for working on the go. Microsoft 13.8\" Surface Laptop Copilot+ PC $1,199.99 4.6 (1K+) Microsoft 13\" Surface Laptop Copilot+ PC $899.99 $999.99 4.6 (135) How to choose the right budget laptop for you To find the best option for your needs, consider the following trade-offs: Feature Best for... Compromise ASUS Vivobook 16 All-around value and storage capacity. Heavier and less portable than the Surface Laptop . Acer Aspire 14 AI Creative tasks and premium build quality. Potentially higher price point than other budget models. Microsoft Surface Laptop Portability, battery life, and durability. The Snapdragon processor has limitations with gaming and high-end software.",
        "parse_status_code": 12000
      },
      "created_at": "2025-09-01 13:40:38",
      "updated_at": "2025-09-01 13:40:51",
      "page": 1,
      "url": "https://www.google.com/search?udm=50&q=high+quality+and+best+performance+budget+laptops&uule=w+CAIQICINdW5pdGVkIHN0YXRlcw&gl=us&hl=en&sei=XKK1aN7PF42_5OUP9taB4A0",
      "job_id": "7368276605665288193",
      "is_render_forced": false,
      "status_code": 200,
      "type": "parsed",
      "parser_type": "",
      "parser_preset": null
    }
  ]
}

5. Bonus: localize results

As Google AI Mode is supported internationally, you may also want to scrape localized AI responses. You can do so by adding the geo_location parameter and setting it to the supported geolocation.

payload = {
    'source': 'google_ai_mode',
    'query': 'high quality and best performance budget laptops',
    'render': 'html',
    'parse': True,
    'geo_location': 'United Kingdom'
}

Benefits of scraping Google targets

Scraping Google AI Mode is powerful on its own, but the real advantage comes when it’s combined with other Google data sources. 

For example, pairing Google Finance with AI Mode allows investors or analysts to see both the hard search data (stock prices, market movements) and the narrative layer (how Google’s AI summarizes news about a company). This combination reveals not just what is happening financially, but also how the market conversation is being shaped.

Similarly, scraping Google Lens alongside Google Search results can uncover how visual content influences online visibility. Imagine a brand tracking its product images: Lens provides data on how those images are recognized and categorized, while Search shows how they rank in traditional listings. Together, they highlight opportunities to strengthen both visual branding and SEO.

Another valuable pairing is Google Trends with People Also Ask. Trends shows what topics are surging in popularity, while People Also Ask uncovers the exact questions users have. By combining them, companies can predict rising consumer needs and create content or products that directly address those questions before competitors do.

Travel and hospitality businesses can benefit from connecting Google Flights, Hotels, and Maps data. Flights reveal pricing and demand shifts, Hotels show availability and competitiveness, and Maps brings in local context with reviews and business details. This triad paints a complete picture of tourism flows, helping companies adapt pricing strategies or expand into new markets.

Even in academia or R&D, linking Google Scholar and Google News with AI Mode is valuable. Scholar provides authoritative research, News shows how those findings are being reported, and AI Mode distills it into summaries. Together, they help researchers track both the discoveries and their public interpretation.

When looked at individually, each Google target offers useful but fragmented insights. When scraped together, especially with AI Mode as the interpretive layer, they provide a 360-degree view of information ecosystems, blending raw extracted data with context. This multi-source approach equips businesses, researchers, and marketers with valuable insights needed to stay competitive in fast-changing environments.

Wrapping up

Scraping AI Mode, especially when combined with other Google targets, allows businesses and researchers to stay ahead of the curve. In a world where information is constantly shifting, tapping into this AI-driven layer of search is not just useful – it’s becoming a necessity.

If you’re interested in how AI is changing the data acquisition environment, take a look at our website: 

• LLM Training Data: The 8 Main Public Data Sources

• Data for AI & LLMs

And if you're curious about scraping other Google targets not mentioned in this article, check out our tutorials:

• How to Scrape Google Shopping Results: A Step-by-Step Guide

• How to Scrape Google Images With Python

• Scrape Google data with Web Scraper API