Think about the late 2000s and early 2010s! With the smartphones being introduced, they triggered the first “app boom”. It came as the gold rush that has fundamentally changed how we live, work, and play. The feeling it implored was that of “once-in-a-generation shift”. But now, gear up – the second phase of the app boom is already underway. This time, a new hardware piece is not the catalyst – relatively, a revolutionary new form of intelligence called Generative AI.

The core of this new boom is not solely about adding a “smart” feature to the existing app. Rather, it is all about reimagining completely what an app can be! Generative AI has proven to be helpful! It is making the process faster, cheaper, and easier for building incredibly sophisticated, hyper-personalized software. By eliminating old hindrances and creating entirely new markets, GenAI is driving a renaissance in app development. But it is in its early stages.

Key Takeaways

• Generative AI plays the role of a strategic co-pilot
  Using Generative AI tools throughout the software lifecycle, app developers can automate routine tasks such as coding, debugging and documentation.

Experience Prasarnet’s expertise to boost your brand’s visibility

• Proven keywords and content strategies to improve search rankings

• Drive consistent growth, generating qualified organic traffic.

• Optimize digital presence to strengthen brand credibility.

Book a Call

• App developers upgrade into strategic innovators
  With the convergence of Gen AI and low-code platforms, developers can take up strategic roles. They closely align digital solutions with the business objectives.
• Low-code platforms raise speed and collaboration
  Developers will now use Gen-AI-enhanced low-code/no-code frameworks to prototype and experiment quickly.
• Transition to strategy from execution
  Developers can participate in shaping products and services by automating repetitive tasks. They can now forgo more substantial alignment between tech implementation and business goals.

What is adding to the strength of this new app revolution?

The first app boom was built on the foundation of the iPhone and the App Store. Because of this, the world got its hardware and distribution channels. But the second app boom’s building and development is based on Large Language Models (LLMs) and other generative models. Admittedly, these search engines can understand and generate human-like texts, codes, images and audio.

In the first wave, existing services like maps, banking, and social media were integrated into users’ pockets. On the other hand, the second wave revolved around creating a complete set of new capabilities. We can consider it as the difference between a tool and a collaborator.

Learn More

While an old map shows the way, a GenAI-powered travel app plans the entire vacation by following a simple conversation. This fundamental shift is the new essential for creating this immense opportunity.

Putting the barrier down: From a simple idea to the app in record time

Democratized development is among the most significant impacts of GenAI. Earlier, to build a complex app, certain necessities were compulsory. Only a large team of specialized developers, designers and a good deal of funding could complete it. But today, GenAI has begun leveling the playing field.

Proof of this is AI-powered tools such as GitHub Copilot are built with fruitful traits. These are capable of writing code, suggesting bug fixes, and even translating code from one language to another. Definitely worth being counted as a massive productivity boost!

Key insights:

As per a 2023 GitHub study, developers are 55% faster to complete tasks when they use GitHub Copilot. Hence, it means a solo entrepreneur or a small team can build and launch products, although they will always need to invest in a certain amount of venture capital.

Due to this speed, rapid prototyping and iteration have become possible. Nevertheless, app development is just half the battle. For the app to succeed in the crowded market, users will have to discover it in the Apple App Store and Google Play Store. Visibility is paramount in this new digital ecosystem; hence, the assistance from a specialized generative engine optimization agency is a proven game-changer. The GenAI experts ensure someone discover these innovative apps correctly through AI-driven search and discovery platforms.

Hyper-Personalization – An app built just for the users

Generic experiences are now stories to be left behind! Today’s users expect apps to understand and adapt to their personal needs. GenAI can accomplish tasks on a scale not seen before. Other than one-size-fits-all interfaces, apps will now create a dynamic, one-of-a-kind experience for every single user.

Learn More

A few instances to imagine:

• A language-learning environment. Here, an AI tutor conducts honest conversations with users, adapting its difficulty and topics to the users’ progress.
• A wellness app with an AI coach. It has the capability to craft daily routines based on sleep data, stress levels and verbal feedback.
• A shopping app features an AI assistant. It displays desired products to users and helps find the best match for a specific circumstance.
• Key Data – As per McKinsey, 71% of consumers expect companies to deliver them personalized interactions. The key to meeting this demand is GenAI.

As apps become more conversational and personalized, traditional marketing funnels are breaking down. Making these unique, AI-driven features discoverable calls for a new approach to SEO. This leads forward-thinking startups to seek out generative engine optimization services to ensure their personalized content effectively connects with the right users.

Have a question for our branding experts?

Get in touch with us

Let us talk about your project goals

• Designing brand strategy
• Brand identity development
• Market research & competitor analysis

Free Quote

The introduction to an entirely new app category

Rather, this app boom presents a most striving aspect. GenAI not only improves existing app categories but also creates new ones from scratch. Just a few years ago, the scene was all different! It limited the idea of a mainstream AI art generator or a personal AI companion to science fiction. But today, apps like Midjourney, Jasper, and Character.ai have become household names with millions of users.

Key data:

The rapid growth of these platforms proves the market demand. ChatGPT has reached 100 million monthly active users within two months of being launched. It is a record-breaking pace, demonstrating the massive appetite of the public for AI-powered tools.

These apps are the representations of a new frontier. We cannot simply call them tools, for they are our creative partners, assistants, and companions. In today’s increasingly competitive market, standing out is crucial. Hence, partnering with the right generative engine optimization company is more than a marketing decision. Doing it makes up a core business strategy for capturing and retaining users in this fast-evolving landscape.

Conclusion

The birth of a new era of software! The second app boom is setting in. Hence, it is far more than just being a tech trend! Consider it the fundamental shift driven by the creative and intellectual horsepower of Generative AI. GenAI is bringing out a wave of innovation meant for redefining the next decade of software. It has been possible with the barrier to entry being minimized, true hyper-personalization being enabled, and entirely new product categories being created. The future is not just coming for the developers, entrepreneurs and users – everyone is building it! Just with one prompt at a time.

An honest confession is that the digital marketing world has prioritized the #1 spot on Google for years. It had served as the promised land of clicks, traffic, and conversations. However, since early 2025, a close analysis of analytics reveals a tremor. The tremor is the global rollout of Google’s AI overviews, and the aftershocks are now being measured. Then what is the headline-grabbing statistic? A staggering 32% drop in Click-Through Rates (CTR) for the top organic result.

For several small business owners and large enterprises worldwide, this has been a gut-punch. The prime real estate, which has been achieved through so much battle, now suddenly becomes improper. However, it is not an obituary for SEO – instead, we should name it a call to evolution. Due to this significant shift, now the demand is for a more innovative, more agile approach to how search and traffic are viewed.

Key Takeaways

• The new throne to SEO
  Achieving the #1 spot on Google is no longer the ultimate goal. A brand’s real win is when it wears the crown by being quoted in AI Overviews – where AI pronounces the brand’s name.

Experience Prasarnet’s expertise to boost your brand’s visibility

• Proven keywords and content strategies to improve search rankings

• Drive consistent growth, generating qualified organic traffic.

• Optimize digital presence to strengthen brand credibility.

Book a Call

• Written for humans, optimized for AI
  AI will be compelled to choose straightforward, conversational and structured content. AI can hardly resist the information.
• Authority is the new oxygen
  Experience, expertise, authoritativeness and trustworthiness are now the passport into AI-generated summaries. We cannot treat E-E-A-T as merely a buzzword.
• Questions are absolute gold!
  AI has its preferred sweet spots to summarise – long-tail queries, FAQs, and Q&A formats.
• Structure’s voice is louder than the keywords
  AI can better understand and display your content when the content has Schema markup, headings and intent-driven phrasing.
• Future-proof your brand’s visibility
  Tomorrow’s SEO is concerned about the brand being the source AI trusts to talk about. So, why chase only the clicks?

The “Why” Behind the Great Click Diversion

Did all the clicks vanish? Well, the inquiry and answer are straightforward – the clicks have not taken off. Before the users have clicked, they have already found the answers to their queries.

Learn More

Google’s AI Overviews have been designed to provide direct, synthesized answers to user queries right on the Search Engine Results Page (SERP). When a user raises a question, ” How to re-pot a monstera plant?”, they receive more than just a list of links; instead, they get a neat, AI-generated paragraph that properly explains the steps. Often, the summary is so comprehensive that it elates the users, and they get no reason to click through to an article.

Therefore, this data highlights a clear trend:

Top result Impact

The traditional #1 organic position has experienced a CTR decline of nearly a third, from approximately 28% to around 19%.

Informational queries that hit hardest

What suffered the most significant declines include the “How-to”, “What-is” and the list-based queries.

Navigational and transactional queries

These have undergone much less effect. The users searching for a particular brand (say, for example, “AI marketing company in India”) or for buying a product (“purchase black sports shoes) are still more likely to click on a link to complete their task.

Having pointed out these pointers, what deserves a mention is that Google is not being malicious. This is the age of natural evolution of search. The overall goal is to provide the best user experience. For many queries, the best experience is a direct answer.

The New Playbook – a Note on Adapting and Thriving in an AI-first World

Panic will never help. It is a failing strategy. However, even if the game has changed, it is not yet over. The focus now has to shift from just ranking #1 to becoming the source of truth for the AI. So, the forward-thinking strategy gains ground since it will start ruling soon.

Learn More

1. Aiming for the AI snippet (Our new #0 spot)

The new primary goals are to feature the content in the AI Overview itself, as it represents the new pinnacle of visibility. Now, to get it done, the content should be:

a. Clear and concise

Structuring content written in simple language, with clear headings (H2s, H3s) and bullet points and numbered lists.

b. Factually accurate and authoritative

Google’s algorithms and its AI are heavily reliant on E-E-A-T (Experience, Expertise, Authoritativeness and Trustworthiness). Sources need to be cited and linked to authoritative studies to establish credibility.

c. Directly answering the question

Structuring the content provides a direct answer to a specific user query early on.

2. Taking up long-tail keywords and nuanced queries

AI overviews are superb at answering common questions, but they are likely to struggle with particular, complex, and nuanced topics. Here comes the opportunity. Targeting the long-tail keywords that dig deeper into a subject is the game-changer. Other than “SEO tips”, it is wise to target “advanced schema markup for B2B tech services in 2025”. When a user has such a specific need, they will most likely bypass the AI Overview and look for an expert resource.

3. Partnering with an AI-focused marketing agency

The days of basic keyword insertion and link building are now insufficient. In the current digital landscape, how AI models process information requires a deep understanding. It requires the assistance of an engaging professional service to be at a competitive advantage. An AI marketing agency conducts traditional SEO and also understands the differences in this new environment.

When a brand works with an AI digital marketing agency or a specialized AI advertising agency, then its strategy will pivot effectively. An upgraded AI-based SEO service focuses on technical SEO, structured data (Schema markup), and content strategies designed to be machine-readable and AI-friendly. A top-tier AI marketing company helps brands identify these new opportunities and reallocates their resources for maximum impact.

Have a question for our branding experts?

Get in touch with us

Let us talk about your project goals

• Designing brand strategy
• Brand identity development
• Market research & competitor analysis

Free Quote

Looking Beyond the Click to Redefine Success

With the declining CTR, now it is time to broaden the definition of success. Let us look into the new metrics of influence:

Brand mentions in AI Overviews

When a brand is cited as a source in an AI answer, it makes a powerful branding, even without a click. It helps in developing authority and trust.

Increased brand searches 

After seeing the brand appear in an AI Overview, the user might not click, but later proceed to search the brand directly.

Conversion rate from organic

The earned traffic may be more qualified. These are the users whose needs AI did not meet – hence, they are having more complex problems and in all probability, are further down the buying funnel.

Finally

Look at it in the light of an evolution, not an extinction. The 32% CTR drop is the seismic event in the sphere of SEO. It’s quite justified to feel concerned. Nevertheless, Search Engine Optimization has not yet died down. Answer Engine Optimization has taken birth. The fundamentals of creating high-quality, authoritative and user-centric content have become more critical than ever.

Now, the challenge is packaging the content in a way that is appealing to human readers and Google’s AI. To navigate this new terrain and discover new pathways to success, start adapting your strategies with a focus on becoming an authoritative source and leveraging expert help. With the top spot changing, it is time for the strategy to be upgraded as well.

Headed to the new era of AI and web crawling! The continuing evolution of Artificial Intelligence (AI) has caused search engines and large language models (LLMs) to become more reliant on web content for training and improving their algorithms. To respond, Google has introduced the LLMS.txt file – an evolving protocol designed for helping the web admins control how AI systems access their data. Google has now suggested that using a noindex HTTP header along with LLMS.txt makes it a practical move in specific scenarios.

However, in this article, we have discussed the reasoning, use cases, and best practices according to Google’s recommendations that digital marketing experts should follow.

Key Takeaways

• LLMs.txt – AI’s new robots.txt (Blueprint for AI crawlers)
  Similar to robots.txt guiding search engines, LLMs.txt is emerging as the file that instructs Large Language Models (LLMs) on how to use a site’s data.

Experience Prasarnet’s expertise to boost your brand’s visibility

• Proven keywords and content strategies to improve search rankings

• Drive consistent growth, generating qualified organic traffic.

• Optimize digital presence to strengthen brand credibility.

Book a Call

• Noindex Header – A classic tool built with new power
  The noindex tag is still important. LLMs.txt directly speaks to AI. Noindex ensures the content is not coming up in traditional search results, if chosen so.
• Two shields are needed. Not one
  A dual-layer defence is created with combined LLMs.txt with noindex. While one manages AI’s scraping method and learns from content, the other controls the search engine’s way of display.
• Content control means brand power
  Content can be easily absorbed, summarized and rephrased in the AI-driven world. With these strategies, a brand’s content is ensured of ownership, visibility and control over how the intellectual property is appearing.
• Openness and protection in a balanced scale
  Business’s decision should be whether AI models will be allowed to use their content to spread brand authority or should the content be guarded for exclusivity protection. A strategy enabling one to choose the middle ground.
• AI Governance is SEO’s future
  SEO is now more than visibility – it is about governing how AI systems are accessing and representing a brand’s content. Name it SEO 2.0 with legal and ethical layers built in.

What does LLMS.txt mean?

Similar in concept to robots.txt, LLMS.txt has been designed with the specific purpose to control the access of LLMs (such as ChatGPT, Claude, Gemini) to a website. Nevertheless, it is not yet an official standard, but LLMS.txt allows the publishers to declare how the AI models will be able to use their data, to prevent unwanted scraping or dataset inclusion.

What are the key capabilities of LLMS.txt?

As a rule, here are the key highlights of the benefits of LLMS.txt:

• AI crawlers are allowed or disallowed by specific agents.
• Protecting proprietary or sensitive content from being used to train datasets.
• Customizing AI access policies at the domain or path level.

Learn More

What does the Noindex Header mean?

The noindex HTTP header is the server-sent directive informing the search engine crawlers not to index a particular page. Unlike meta tags in HTML, HTTP headers are sent before any content loads, making them a practical and often invisible method to manage crawler behaviour.

What are the chief capabilities of the Nonindex header?

Generally, these include the capabilities of the Nonindex header:

• Blocking a search engine from displaying a specific page or file in search results.
• Preventing indexing for non-HTML files, such as PDFs, images and other documents.
• Allowing for efficient, server-level control over indexing rules for the complete site sections.

For instance:

• http
• CopyEdit
• X-Robots-Tag: noindex

This header helps in preventing a page from being indexed, despite its content.

Why does Google suggest pairing Noindex with LLMS.txt?

Google has clarified in recent discussions that while LLMS.txt instructs AI crawlers on behaviour, it does not necessarily prevent a page from being indexed by Google Search or any other engines. In that case. here is where the noindex header enters.

The merits of combining Noindex with LLMS.txt

Let us now discuss the key benefits of combining Noindex with LLMS.txt.

1. LLMS.txt takes control over the AI crawlers, and not the search indexing

The llms.txt file has been designed to manage access for large language model (LLM) crawlers, such as GPTBot (OpenAI), ClaudeBot (Anthropic), and GeminiBot (Google). It instructs these bots on which parts of a site they are permitted to crawl and use for training AI models.

Nevertheless, LLMS.txt does not influence how search engines index content. A page could still appear in Google Search results, even if AI bots are disallowed from accessing it.

2. Noindex helps in preventing search engine listing

On its reverse side, the noindex directive informs search engine crawlers, such as Googlebot, to exclude the page from their index. Consequently, it indicates that even if a search engine visits a page, it will not appear in search results if the noindex header or meta tag is present.

3. Combining Noindex with LLMS.txt provides complete content protection

As per Google’s recommendation, pairing the two is advantageous because:

• LLMS.txt protects AI training data collection
• Noindex is a protective tool against search engine exposure

Together, they bring up a dual-layered control – one over AI models’ way of using content, and the other over visibility in search engines. This is particularly important for content publishers, research sites, or proprietary platforms that aim to restrict both access and discoverability.

When should the Noindex header and LLMS.txt be used?

To prevent a specific webpage from appearing in traditional search engine results, such as Google Search or Bing, the Noindex header should be used. LLMS.txt should be used when Large Language Models (LLMs) are to be prevented from using the content on the website for training purposes.

Furthermore, these two directives serve different purposes, controlling access for various types of web crawlers.

Learn More

Noindex Header

The noindex directive is a meta tag or HTTP response header that instructs search engine crawlers not to include a particular page in their search index. It should be noted that its focus is on public search visibility.

How does the Noindex Header work?

A meta tag in the <head> section of HTML is placed, or the server is configured to send an X-Robots-Tag HTTP header.

• HTML Meta Tag – <meta name = “robots” content = “noindex”>
• HTTP Header – X-Robots-Tag: noindex

When to use Noindex Header?

Here are the worthy instances of using the Noindex Header:

• Staging or development sites
  For keeping your in-progress versions of pages out of public search results.
• Internal pages
  For all login pages, employee-only portals, or other pages not for the public’s use.
• “Thank You” pages
  Confirmation pages after a form has been submitted, and no further searching is needed.
• Thin content
  Pages with little unique value are likely to negatively impact the site’s SEO.
• Sensitive content
  Pages with information that should be accessed through a direct link but not be discovered through search.

LLMS.txt

LLMS.txt is the proposed, but yet-to-be universally adopted, extension to the Robots Exclusion Protocol (REP). Its primary goal is to empower website owners by giving them control over whether their content is used for training generative AI models. Clearly, it focuses on the amount of data AI crawlers use, rather than search indexing.

How does LLMS.txt work?

It is the txt file and is similar to robots.txt and is placed in the website’s directory (for instance “awe” s “”e” .co”/” lms.txt). It specifies the rules for crawlers associated with LLMS. Though the exact syntax and universal standard are continuing to evolve, the common proposal is:

User-agent: *
Disallow: /

User-agent: Google-Extended
Disallow: /

This example illustrates Google’s use of an agent for data collection in its AI models. When it is disallowed, it prevents the content from being used for training purposes.

When to use LLMS.txt?

LLMS.txt is to be used in these cases:

• To protect the copyrighted material
  For explicitly stating that a brand’s creative works, like the articles, images and codes, should not be used in training the AI models.
• Safeguarding proprietary data
  In case the site contains unique datasets, research, or business information that should not be ingested by third-party AI.
• Control maintenance
  As the general measure of the site’s usage procedure, it is controlled beyond simple web browsing and search indexing.

To briefly summarise, Noindex is used for search engine visibility, and LLMs.txt (or any similar directives in robots.txt) is used for AI model training data.

Have a question for our branding experts?

Get in touch with us

Let us talk about your project goals

• Designing brand strategy
• Brand identity development
• Market research & competitor analysis

Free Quote

The considerations and limitations to take note of

While noindex and llms.txt provide stronger control over content usage and display online, they are not foolproof. These are a few key considerations to understand:

1. LLMS.txt has not been standardized yet

The LLMS.txt file is just a new and informal proposal. It is not a web standard like robots.txt. Hence, not all AI crawlers could support or respect it, particularly the ones from smaller or non-compliant companies.

2. Noindex does not block access

The noindex directive helps prevent indexing; however, it does not prevent crawlers from accessing or reading the content. In case a bot ignores the indexing rules, it still retains its ability to scrape the data. For entirely blocking access, here are what to consider:

• robots.txt disallow rules
• IP blocking or authentication
• CATCHAs or bot detection systems

3. Caching and third-party rehosting

Even after applying noindex, third-party platforms such as archive sites, social media previews or AI datasets that had previously been trained on the site could still store cached versions of content. With no easy fix available, the only options are takedown requests or legal actions.

4. Performance overhead

Proper server configuration is necessary when adding HTTP headers such as X-Robots-Tag. On the misconfigured servers, this is likely to cause caching issues or unexpected behaviour, as it is handled without care.

5. The crawler’s decide enforcement

Both LLMS.txt and noindex are dependent on the crawler choosing to prioritize the directive. While Google and OpenAI generally respect these signals, the bad actors or rogue crawlers could ignore them entirely.

Conclusion

AI will continue to evolve, and our tools to control content usage should also become more advanced. Pairing LLMS.txt with a noindex HTTP header enables webmasters to better manage both search engine visibility and AI crawler access. While LLMS.txt continues to gain adoption, combining it with the traditional directives like noindex will provide an added protective layer. This is a forward-thinking step for businesses and creators as well, toward responsible AI content governance.

Web browsers have been our steadfast, loyal window to the digital landscape for years. The fundamental job of web browsers to aid digital branding, from Netscape Navigator to Google Chrome, has been to bring and display web pages. After typing the keywords into the search bar, users would sift through a list of blue links and do all the heavy lifting on their own. Now that era seems to come to a close. With the emergence of the new generation of AI-powered browsers, users’ relationship with the internet is undergoing a promising transformation from manual search to intelligent conversation.

Apart from being standard browsers with a few AI extensions added, the AI web browsers have been developed from the ground up, with artificial intelligence at their core. While these AI web browsers are mining information, they are also equally capable of understanding, synthesizing, and presenting it effectively. In this guide, we have briefed the world of AI browsers important to an AI digital marketing agency, from the pioneering “answer engines” to the future of “AI-driven commerce”.

Key Takeaways

• AI browsers have become smarter gatekeepers
  AI browsers are not only displaying the pages, they are interpreting, summarizing and personalizing web content.

Experience Prasarnet’s expertise to boost your brand’s visibility

• Proven keywords and content strategies to improve search rankings

• Drive consistent growth, generating qualified organic traffic.

• Optimize digital presence to strengthen brand credibility.

Book a Call

• From search to answers
  AI browsers deliver direct insights. Hence, users depend less on search engines.
• Contextual intelligence
  AI browsers understand intent, not only the keywords. Hence, AI produces highly relevant results.
• Productivity boosters
  User efficiency is being redefined by automated summarization, voice queries and task integration.
• The new SEO frontier
  Brands have to adapt to ensure both humans and AI browsers are easily digesting their content.

What does AI Browser mean?

An AI browser is tasked with reimagining the entire process of accessing information online. It will not act as a simple file-fetcher; instead, it will perform the role of a research assistant. The core point of distinction is its ability to process natural language and understand context.

For instance, when the users are conducting research on sustainable energy sources, this is the picture:

Traditional Browser:

The search is for “advantages of solar power”. The user opens five tabs, skims each article for key points, and then manually compiles their notes.

AI Browser:

The user asks the search engine, “What are the main advantages and disadvantages of solar power, and which countries are leading in its adoption?” After scouring the Web, the browser reads multiple sources and returns a concise, synthesized answer complete with citations.

Learn More

These AI web browsers have been developed using Large Language Models (LLMs) – the same technology employed by ChatGPT. This enables them to move beyond the keywords to comprehend content, so that the Web can work for the users, and not the other way around.

What are the core features powering the search revolution?

AI browsers are distinguished from traditional browsers by a series of robust features that extend beyond simple search.

a. Conversational search and summarization

The basis of the AI browser is that it is capable of asking complex questions in simple English. The AI provides direct answers. Often, it summarizes lengthy articles, technical papers, and user reviews into easy-to-understand bullet points.

b. Proactive organization

Many AI browsers are capable of automatically organizing digital life. For instance, Arc Browser utilizes “Spaces” to separate work from personal projects. Opera One’s “Tab Islands” feature can automatically group related tabs. Through this AI-driven clustering, clutter is reduced and focus improves.

c. Creating content on-the-fly

When users need to draft a professional email or a social media post based on the article they are reading, integrated AI assistants, such as Microsoft Copilot or Brave’s Leo, can do it directly within the browser window.

d. Contextual understanding

All these AI web browsers can understand the content that users are reading on the page. Highlighting a technical term, the users can ask for an explanation, or ask the browser to “summarize” the key arguments on this page, without having to leave the tab.

The key players in the AI Web Browser space

This field’s rapid expansion is welcoming both new startups and established big names vying to define the Browse’s future.

1. Perplexity

Perplexity is often termed as “Answer Engine”. This tool excels at providing direct, accurate answers with in-line citations. After users ask a question, it provides links and a comprehensive summary synthesized from top sources. Perplexity Comet is its latest fast and conversational model that has been designed for real-time dialogue, so that research feels like a conversation with an expert.

Learn More

2. Arc Browser

Arc, from the Browser Company, has gained a cult following for its fresh user interface, replacing the top bar with a dynamic sidebar. Its AI features, branded “Arc Max”, are capable of renaming the tabs and downloaded files for clarity, generating 5-second previews of links by hovering over them. It allows users to ask questions directly about the webpage they are visiting.

3. Microsoft Edge

With Copilot being integrated (as is powered by OpenAI’s GPT models) directly into the sidebar, Microsoft has introduced AI Browse to the mainstream. With DALL-E 3, the edge users can summarize pages, compose texts and also generate images. They don’t need any separate tool. Being deeply integrated with the Windows OS, it is now a powerful, built-in assistant.

4. Google’s AI in Chrome

Since Google is the world’s most popular browser, Chrome’s onset into AI bears immense significance. Apart from a single mode, Google has embedded a suite of experimental AI features powered by its Gemini models. It comprises a “Tab Organizer” that automatically creates groups, a “Help me write” tool to compose texts anywhere on the Web, and AI-generated browser themes. Through these features, generative AI capabilities are directly brought into the familiar Chrome experience.

5. Brave Browser

Brave is a compelling alternative for all privacy-conscious users. By integrating its native AI assistant, Leo, it helps users by summarizing pages and answering questions similar to its competitors. Focus on privacy is Brave’s key differentiator. Leo’s requests are proxied to anonymize user data. For model training, it does not make use of conversations. Hence, it offers a more private AI experience.

6. Opera One and the Vision of Opera Neon

Opera has rebuilt its flagship browser as Opera One, which is centered around its native AI assistant Aria as well as an innovative “Tab Islands” feature for contextual grouping. Nevertheless, Opera’s spirit of innovation had been showcased long ago with the introduction of Opera Neon. It was released as a concept browser in 2017, and Neon evolved into a visionary experiment, rather than a daily-use product. Featuring a physics-based engine, chat-bubble-like tabs and a split-screen mode, Opera Neon could predict the highly visual and integrated future which browsers now prefer. Neon had been a glimpse into the future, and its DNS can be noticed in the dynamic designs of present-day AI browsers.

7. SigmaOS

This browser functions as the productivity workspace. It has been exclusively built for macOS. SigmaOS treats the browser as the operating system for users’ work, hence it is taking a radical approach. It has completely eliminated the traditional horizontal tabs in favour of “Workspaces”. Pages are in vertical organization inside a workspace, almost similar to a task list. Users can mark pages as “done” to clear them or “snooze” them for later. This design fosters a more deliberate and focused workflow. Airi is its AI companion, which is seamlessly integrated into this structure. As the users press a keyboard shortcut, they can ask Airi to summarize the page they are on, draft an email reply, or explain a complex topic. This is how it effectively acts as the co-pilot for productivity within its highly structured environment.

Have a question for our branding experts?

Get in touch with us

Let us talk about your project goals

• Designing brand strategy
• Brand identity development
• Market research & competitor analysis

Free Quote

The next step – From generating information to action with ChatGPT shopping

AI’s ultimate goal is to move beyond retrieving information to performing actions on behalf of users. Here, features such as AI-powered shopping assistants are needed, even if it is not a standalone browser. The capabilities demonstrated by models like ChatGPT point to the future of E-commerce within the browser.

For instance, while looking for a new pair of running shoes – other than manually comparing dozens of models across various retail sites, the users can simply tell the browser to “Find a neutral running shoe for marathon training under $200, with good cushioning. Compare the top 5 options and summarize their reviews”.

Then the AI will –

• Start scanning multiple E-commerce sites
• Filter the products based on specific criteria (neutral, cushioning, and price)
• Read and synthesize numerous user reviews
• Provide a comparison table that highlights the pros and cons of the top five models

This is how the browser is transformed from a passive portal into an active, intelligent shopping agent that is time-saving and helps users make better decisions.

Wrapping up

The users are presented with a smarter partnership with the Web. AI web browsers represent a fundamental shift in how users interact with information. They are converting the chaotic, sprawling Web into a coherent, personalized resource. AI handles the tedious work of searching, filtering, and summarizing to keep users’ cognitive energy free to focus on what truly matters – understanding, creating, and making informed decisions. The journey from simply clicking on a link to sophisticated, AI-driven conversations and actions is well underway. Now, the browser is not only restricted to a window, but it has also become an intelligent partner for navigating the digital world.

Introduction

AI Chatbots or virtual assistants are specialized programs designed to mimic human customer support. They are trained by AI and machine learning algorithms on customer and product bases to resolve customer queries in natural language processing (NLP).

Several sectors, including retail, healthcare, insurance, government agencies, defense, and automotive, utilize AI chatbots that form a valuable and intrinsic part of customer service and support. You can find them as chat boxes on websites and are available at a click.

Since AI chatbots are connected to information, product, and service repositories, they rapidly access information to answer customer queries. Market Research Future highlights that by 2034, the AI chatbot market is expected to reach nearly $34 billion USD. This blog examines the rise of AI chatbots and their impact on transforming customer support and sales.

What are Chatbots?

AI chatbots are new avatars of chat services, replacing human operators. An AI program replaces human operators with a human-like name and avatar. Figure 1 illustrates how chatbots operate.

Users generate queries in natural or everyday language, and the AI chat uses NLP to understand the meaning and intent. The AI platform features a knowledge base and data storage repositories that store frequently asked questions and their corresponding answers. The system searches the databases and presents the appropriate answer. With constant learning and feedback, these responses are refined.

Several types of chatbots have been developed. Some of the popular kinds are rule-based, machine learning-based, retrieval-based, generative, task-oriented, and conversational. Organizations choose the appropriate chatbot to meet their needs.

Functions of AI Chatbots

AI chatbots are programmed to orchestrate processes, technology, brand promotion, people, and business objectives. They are designed for specific functions such as answering customer questions, running searches based on user inputs, analyzing data, and understanding the intent of a query.

AI chatbots understand the emotion and context of conversations and make recommendations in multiple languages. They can track orders, provide updates, assist with configuration and troubleshooting, and serve as a human support.

How AI Chatbots transform customer support and sales?

AI chatbots are integrated with customer relationship management applications. This section presents 15 ways in which AI chatbots transform customer support and sales.

1. Reduced costs

The use of well-trained AI chatbots can reduce the number of human support staff. AI chatbots can handle multitasking, allowing them to respond to multiple requests from users simultaneously.

Human support would place customers in a waiting queue until a representative is available. In addition, AI chatbots reduce the need for office space, commute, training, and other expenses that a firm would spend on human support. These features reduce costs.

2. 24×7 availability

AI chatbots are integrated with the website or app and are always available. Customers use mobile apps or the site to open the chat box and ask questions. There is no need for human support to manage the bot. As a result, customer support is available 24/7, including nights and holidays.

Sales staff and the management are assured that support is always available, in multiple languages. This assurance is essential, as online customers can make purchases at any time when human staff are not present. Therefore, the 24/7 availability transforms customer support.

3. Personalized service

Customers differ in their requirements and preferences. In such cases, it is important to know what items interest each customer. AI chatbots track browsing behavior, including items customers viewed, pages they visited, and problems they encountered.

As a result, AI chatbots recommend specific products or services based on customers’ previous patterns. The chatbots can then send alerts when items customers have expressed interest in become available or are discounted. Personalized service is available in this manner.

4. Faster and accurate responses

AI chatbots utilize advanced architecture and a knowledge base that enable the rapid processing of unstructured user queries. Using NLP, they quickly process text classification, dialogue management, machine learning, and backend services.

Depending on the query complexity and internet speed, chatbots typically give instantaneous responses. If queries are unresolved, they are escalated to a human supervisor. They also analyze responses to evaluate response times, error rate, and other metrics to improve.

6. Multiple channel support

Many firms utilize multiple channels for communication, and AI chatbots are integrated across these various channels. They deliver consistent and standardized performance across Meta, web, Instagram, and all other platforms and channels.

Customers can access the offerings from multiple channels and obtain the same responses. This feature transforms customer support and sales by deriving an appropriate response from the knowledge base. The quality and accuracy of human reactions can vary.

7. Constant learning

AI chatbots are created with machine learning algorithms. The feature allows the chatbot to learn, remember, and refine responses continuously. Expensive training is avoided for human support staff, and errors are eliminated.

With constant machine learning, customer support, and sales can quickly update new terms and features. Alerts in new products are automatically pushed to customers through the CRM application. By avoiding manual training and updates, customer support is transformed.

8. Increased customer engagement

According to recent statistics, 23% of customer care organizations currently utilize AI chatbots to enhance customer support. AI chatbots give prompt and personalized responses. They are available 24/7 in multiple languages. Customers tend to be more proactive when their responses are addressed correctly, and they get the requested information.

When customer experience is satisfactory, it becomes possible to engage customers and increase their interest in additional products. They tend to visit frequently, spend more time browsing, and make a positive purchase decision. These progressions transform customer support.

9. Maintain privacy and security

Customer contact details, purchase transactions, financial information, and credit card numbers are private. These cannot be compromised or misused. AI chatbots only consider the immediate information necessary to answer a query and do not access confidential information.

As a result, privacy and security of customer information are not compromised. Since this information is shared on a need-to-know basis, AI chatbots maintain a high level of security. Customer confidence in conducting transactions increases and enhances customer support.

10. Handling complex queries

AI chatbots can handle multi-thread queries from customers. This term means that they can answer a series of nested queries. They can also handle several customers who query at the same time, allowing one chatbot to manage them.

Human support or traditional chat addresses only single queries from one person. These features increase the offerings and capabilities of AI chatbots. Customer support has been transformed since the number of customers managed has increased, reducing wait times and fostering positive behavior.

11. Automated workflows and CRM

AI chatbots act as an interface between CRM systems and the customers. The CRM system works best when it is automated with minimal staff interference. All processes, such as learning and updating the knowledge base, are automated.

An automated AI chatbot can autonomously resolve queries and use the discussions to refine the process. Customer support staff benefit from automated workflows, as they are freed up to take on other creative tasks, analyze performance, and implement new strategies.

12. Easy scaling

When an organization expands its offerings or enters new countries, AI bots can scale efficiently. The availability of cloud infrastructure, efficient and high-speed data pipelines, allows support to increase their services.

AI chatbots can clone their services to assume new avatars and provide services in multiple languages. So, in the Middle East, the chatbot could be an Arab, and so on. Support can localize its offerings to suit local tastes and requirements.

13. Reasonable cost

These chatbots are expensive and require a high level of expertise. However, the resulting savings in terms of improved customer support and reduced support staff costs quickly pay back the initial investment.

The results justify these one-time costs. Specialist firms utilize the latest tools with NLP to provide comprehensive functionality. A fully functional AI chatbot requires training and development. These are further refined and improved. One-time costs are justified by the long-term benefits they provide.

14. Multiple language support

AI chatbots are coded to understand multiple major languages. This feature is useful since customers come from different nationalities and not all may be fluent in English. By including other major languages such as Arabic, Hindi, and German, a wider range of customers is served.

Customer support finds that this aspect helps to transform their offerings. It would be difficult and expensive to recruit staff who are native speakers of other languages. Consistent and standard responses of offerings, terms, and order tracking are possible.

15. Integration with sales and marketing

AI chatbots are an extension of customer-related services and support. Organizations analyze data from customer conversations to identify issues. They can then use the findings to improve their service levels.

Other departments and functions use the data to resolve urgent issues and gaps in service offerings. While a firm faces several secondary and minor problems, the main issues that receive the most queries are resolved first.

Conclusion

The article examined 15 ways in which AI Chatbots transform customer support and sales. With the rise in competition and crowded markets, AI chatbots provide a streamlined and focused approach to serving customers, thereby enhancing the quality and level of customer service.

AI chatbots, as the name suggests, are built using artificial intelligence, reducing the costs incurred in hiring human support. Since they are connected to a knowledge base, they can rapidly access the accumulated organizational data to answer a range of queries.

They are available 24/7, never take a break, or call in sick. They access customer browsing history and purchases, and provide personalized service. AI chatbots offer accurate and prompt responses while adhering to privacy standards.

The digital landscape is constantly being reshaped by breakthroughs that redefine what is possible – it is in perpetual motion. The advent of artificial intelligence is a proven game-changer among these. However, with the arrival of Gemini 2.5, a pivotal moment ushers in an unprecedented era of productivity and efficiency across virtually every sector. Now it is not only an incremental upgrade, but rather a supercharge – one that is fundamentally altering how everyone works, innovates, and interacts with information.

A Hike In Multimodal Understanding and Reasoning

Multimodal understanding, at its core, is one of Gemini 2.5’s most significant contributions. Previous versions of AI models often struggled to interpret complex combinations of text, images, audio, and video. However, Gemini 2.5 seamlessly processes these diverse types of data to draw connections and extract insights, which the previous automated systems were incapable of handling.

For example, a legal team is reviewing reams of legal documents, video depositions, and audio recordings of client meetings. Gemini 2.5 summarises the key points and identifies critical nuances, discrepancies, and emotional cues across all formats. Hence, the time spent on manual review and analysis is drastically reduced.

Additionally, Gemini 2.5 has enhanced reasoning capabilities, enabling it to go beyond simple pattern recognition. While performing multi-step deductions and understanding intricate relationships within data, Gemini 2.5 even engaged in “adaptive thinking” – it adjusts its approach based on ongoing interactions and feedback. As it follows instructions, it actively solves problems. Thus, Gemini 2.5 is an invaluable partner for carrying out complex tasks that require deep cognitive processing.

Revolutionizing Workflow Automation

Gemini 2.5’s impact on workflow automation is truly transformative. Once, routine, repetitive tasks took countless hours. But these are now being handled with unparalleled speed and accuracy. Starting with automating data entry and generating reports, Gemini 2.5 is liberating human capital from everyday operations, progressing to complex supply chain management and customer support interactions.

Let us consider an example from the manufacturing sector. As Gemini 2.5 analyses sensor data from production lines, it predicts equipment failures before they occur. It even provides suggestions for optimal maintenance schedules, downtime minimisation, and output maximisation. Gemini 2.5 can even perform administrative tasks – it utilises its intelligence to categorise emails, schedule meetings, and draft initial responses. Hence, the employees can focus more on strategic and engaging work. The core is augmenting human labour capabilities, enabling them to achieve more with less effort, rather than replacing human force.

Supercharging data analysis and decision-making with Gemini 2.5

Data is the new oil in this age, and the ability to extract meaningful insights as soon as possible is a competitive imperative. Gemini 2.5 has powered up data analysis, making it more accessible and impactful than ever before. It possesses the capacity to process massive datasets, identify hidden patterns, and generate predictive models, which enhances decision-making at all levels of an organisation.

Upholding creative potential

Gemini 2.5 is the advanced AU, and its most exciting and often debated aspect is its role in generating creative content. It is proving to be an incredible co-creator and accelerator, fueling human creativity. It helps in generating marketing copy and drafting news articles. Furthermore, it assists with scriptwriting and composing music. Gemini 2.5 is capable of producing high-quality, original content at scale.

The overall motive is to assist the human creative in refining concepts, adding their unique artistic touch, and ensuring emotional resonance that can only be provided by human intuition. Gemini 2.5 comes as a partnership to amplify human efforts, pushing the boundaries of what is creatively possible and achievable.

The Collaborative Ecosystem for the Future

The whole of Gemini 2.5 points out a definitive shift in the operative future. The world is advancing towards a collaborative ecosystem – Humans and AI working together as a combined force. Each is responsible for leveraging their unique strengths. AI excels in information processing, task automation, and pattern identification. On the other hand, human minds are masters of critical thinking, emotional intelligence, ethical reasoning, and a differentiated understanding of context that is not yet possible with AI.

In this new era, upskilling and reskilling the workforce to effectively integrate with AI tools is the mantra .Accepting this collaboration and investing in AI literacy is a significant step toward harnessing the enhanced productivity and efficiency offered by advanced models, such as Gemini 2.5. Then, there will be a better scope for success through unprecedented innovation and progress.

Conclusion

With Gemini 2.5 being introduced, the new era of productivity and efficiency has been undeniably supercharged. It is created with advanced capabilities in multimodal understanding, reasoning, workflow automation, data analysis, and creative content generation. These are helpful in reshaping industries and redefining the very nature of work.

While we continue integrating the powerful AI into our daily lives and professional endeavours, the potential for innovation and growth will be virtually limitless. The key is in recognizing AI as an intelligent partner. It is not a human replacement. Instead, AI has been created to enable humans to achieve better outcomes, with a greater impact than ever before.