Five to six years ago, whenever people wanted an answer to a question, they typed it on Bing or Google. Come 2022, and everything changed instantly. Nowadays, people type a question into ChatGPT, Perplexity, or Gemini and get their answers. What does this mean? This means that businesses must show up in AI searches because that is where customers are.
People use AI when searching for their favorite product or service. If the company’s name doesn't pop up in the search results, they have lost millions of customers. By 2028, $750 billion of customer spending will come via AI-powered searches.
80% of customers use AI to conduct 40% of their searches. The change in user search patterns has also changed how traditional search engines work. Organic traffic from traditional search engines has decreased significantly. This drastic shift in search patterns means businesses must find new ways to rank in AI search results. Let’s say a company made every effort to make a mark on AI-generated results. How would they measure the results?
Tracking AI rankings differs from tracking Google search rankings. Also, business owners must also focus on pushing out content that people can find. In this blog, we will cover many aspects related to ranking on search engines.
What are AI Search Engines?
Traditional search engines look for high-ranking keywords in content. Companies tend to use specific keywords to increase their chances of ranking on popular search engines. They add different variations of these keywords and insert them in many sections of the content. These sections include URLs, subheadings, and titles. This further gets the attention of search engines.
In simple language, AI search engines are advanced search platforms. These AI-powered search engines are easy to use. All users have to do is type the question and get quick and concise answers. Such AI-generated answers are personalized, relevant, and easy to understand. Nowadays, users don’t want to wait long to get results for their searches. They want answers quickly.
Browsing through multiple links and finding one with the right answer takes time and effort. AI search engines provide us with the answer in a few seconds. However, these answers may not be accurate all the time. We may have to take them with a grain of salt. More time and research may be necessary to get credible information.
How Do AI Search Engines Work?
AI search engines don’t work like traditional search engines. These search engines are the new breed of search tools equipped with artificial intelligence. Using LLMs (large language models), AI search engines understand queries, read content, and provide straight answers. Compared to Google, which just provides a bunch of links, AI does the hard work. The LLM model understands the user’s request and provides a clear answer.
After gathering data from multiple sources, AI search engines compile a detailed list and provide an accurate and to-the-point answer. Note that AI search engines don’t just blindly answer questions. They also consider the user’s problem, intent, and context. Accordingly, the AI search engines generate answers. While generating answers, the AI search engines consider the following aspects.
- User Location
- Conversation History
- Follow-Up Questions
- Search Style
- User Pain-Points
These answers can be a combination of text, images, documents, screenshots, and more.
AI Search SEO Vs. Traditional SEO
Below is a brief summary of how AI search engines differ from traditional SEO.
Traditional SEO
- Keyword-Focused
- Page-Based Rankings
- Optimized for Crawlers
- Backlinks are major SEO signals
- SERP Competition
AI Search SEO
- Increased focus on meaning and clarity
- Answer-Based Rankings
- Optimized to be understood by LLMs
- Citation Competition
- Brand authority is a stronger signal
Why Should Companies Optimize Content for AI Search Engines?
As mentioned in one of the above sections, many users want quick answers when they type queries on AI search engines. Bearing this in mind, AI search engines provide short and direct answers. Even when users type a query on Google, most of the time, the first response that pops up is AI-generated. After the answer ends, users will see a long list of links.
If the content generated by the user/company is not optimized for AI search engines, it won’t get noticed by many users. Nor does it gain their trust. Most importantly, this limits the company’s revenue opportunities. Traditional SEO searches are becoming outdated. Below are the reasons why companies must optimize content for AI search engines.
1. Greater Visibility
Companies should move in the direction of customer search trends. Customers prefer to search for answers on AI. Instead of providing countless links, AI analyzes vast volumes of information and links on the internet. Then, it creates summaries to provide precise information in the form of answer cards.
If the generated content is meaningful, clear, and authentic, AI search engines may suggest it to users. Companies can benefit from this spotlight. Overall, optimizing content for AI helps direct it to users.
2. Enhanced User Experience for Better Results
AI search engines prioritize content that is short, authentic, and easy to read. When companies generate content in the format that AI search engines favor, it gets recommended to users. Optimized, precise, and meaningful answers result in higher user trust and satisfaction. Based on the experience, users may interact with the company and indulge in purchases.
3. Conversion and Revenue Opportunities
When AI shows content to a user, it also links to the source. This source can be the brand name or the website/webpage link. This may encourage more users to click on the link and visit the company’s websites.
After clicking on the link, users may express interest in the company’s products or services. Inbound leads may turn into loyal customers. Recommending a particular product/service to users gives them the confidence to take the next step.
4. Brand Authority
AI search engines prioritize content that conveys authority and trust. Companies must ensure optimizing their profile to convey their authority. This includes providing information about the following:
- Author Bios
Highlighting the author’s experience and their knowledge about the subject matter.
- Credentials
Specify the writer’s qualifications, certifications, job roles, and experience.
- Transparent Sourcing
Provide links to research, data, and sources. This will help AI check the facts.
- About Page
This section must state what the company does, its track record, and reasons to work with them.
Mentioning the above information helps companies build a reputation. AI search engines will highlight a particular brand/writer.
5. Customer Support
AI can summarize meaningful and relevant content for customers. Examples of such content include user guides, FAQs, and troubleshooting. This reduces the need for employees to provide customer support. It also helps companies acquire more customers because of improved customer satisfaction.
6. Future-Proofing
Not many people search on Google these days. Companies that make the transition from ranking on Google and Bing to AI searches will have an edge over others. Ignoring AI SEO will mean losing out on a huge market share.
7. Multi-Channel Search
AI search engines generate results that include a mix of text, images, and video. Companies must take a cue from this and create content accordingly. Producing multi-modal content means AI will include it to generate results on apps, chatbots, and assistants.
8. Robust Analytics
Optimizing content for AI search engines is a good practice. It results in clear and well-structured content. Good practices include proper headlines and other details, such as the publishing date. Schema markup is also crucial because it tells AI search engines about the content in each section of the page.
When the content is well organized, it enables the analytics tools to understand the content better. Companies get insights into which content performs better. Insights also state parts of the content that people read and skip. This can help companies rethink their strategies and churn out better content. In this way, structuring content better benefits both business owners and AI search engines.
7 Ways to Optimize Content for AI Search Engines
There is no definitive guide on how to optimize content for AI search engines. Surprisingly, LLMs have been around for approximately 3 to 4 years. By now, there should be guides floating around the market on how to optimize content for AI search engines. Sadly, that is not the case. Below are some tried and tested strategies for optimizing content for AI search engines.
1. Ensure Clean and Structured Content
Whether it's people or LLMs, both skim through the first few lines of the content. That is why the content must have a quick summary that tells readers what they can expect. The AI systems also scrutinize the content and find clear answers. Then it puts it right on top where everyone can read it quickly. A strong summary includes three key aspects.
- The summary must be only one to three sentences long. It should directly answer the user’s question.
- State what the user can learn from the content.
- Proceed to the full guide/blog for readers who want a detailed explanation.
Keep the summary on top. Refrain from using jargon in the summary. Include the keyword or the exact (close is also good) query that people search for to increase the chances of getting highlighted. Provide facts and measurable goals. Update the summary if anything changes, such as facts or statistics. AI search engines prioritize content that is relevant and up-to-date.
Group multiple pages or related sub-pages that discuss related topics. This helps AI understand the company’s core strengths and offerings. This will highlight the content as a credible source and show it to users. Make sure to add FAQs at the bottom. Last but not least, use clean formatting. Neither AI nor humans like cluttered pages.
2. LLM-Friendly Formatting
When developing content for AI search engines, keep the content short. The content should not be in huge blocks. Ensure that the content is posted in small, easy-to-read paragraphs. The headings should be such that they match the intent of users. Don’t forget to include examples. These examples will get the point across for AI and humans.
Short paragraphs are easy to read. Breaking down content into different points and headings makes it easy for users to consume. Overall, these little but strong strategies increase the chances of AI recommending the content in response to user queries.
3. Question-Based Sections
Create content with H2/H3/H4 headings that break up the content into different sections. Use question-like queries in these headings. Examples of usch headings include - What is the ___ for? How does help maximize ___? People ask/type similar questions to voice assistants and LLMs. Using questions in headings that mimic real-life user questions helps AI paraphrase the content and provide answers that people want. The LLM models will also provide the source from which they got the content.
Hence, using questions in headings ensures LLMs promote the content. This content will be seen by a larger number of users.
4. Include Stats and Steps
Most AI search engines promote content that they can extract quickly. They also verify its authenticity. So, companies must add statistics, step-by-step guides, and simple frameworks to increase the chances of content ranking higher. Stats add credibility while steps make it easy for AI to summarize the content. Frameworks provide AI with a clear structure to reframe the content when posting answers. Such organized content tells AI what the content is about, lends authenticity to it. Ultimately, AI search engines will promote content as they recognize it as a credible source.
5. Update Content Regularly
AI search engines like content that is latest, accurate, and unique. Hence, companies must make it a point to update content as and when required. This will increase the chances of it ranking on AI search engines. Updating content to include new statistics, research, or providing recent examples to help users understand the topic better.
If the content is accurate and relevant to the current times, it will most likely be recommended and cite the source to users. To sum it up, accuracy and authenticity triumph over AI search engines.
6. E-E-A-T is Key
What does E-E-A-T stand for? It stands for experience, expertise, authority, and trust. Considering this, AI evaluates the content and decides whether to recommend it to users or not. What do AI search engines consider when evaluating a company/user’s content? Does it check for reliability, accuracy, or something else? The answer is below.
- About Page - Details on this page help the AI search engine to verify the authenticity of the company.
- Author Bios - Shows information about authors, along with their credentials, qualifications, experience, and LinkedIn profile.
- External Links - This should include company website links, mentions, and citations from blogs/research papers.
- Brand Mentions - Highlight instances where the company is mentioned online. This includes social media posts, reviews, podcasts, forums, and others.
7. Focus on Schema, Meta-Data, and Machine-Readable Signals
AI search engines depend greatly on structured data. What is structured data? It's a special code that one can add to the content. These special codes tell AI search engines what the content means. It goes beyond the superficial translation. Below are the different types of schema.
- Article Schema - It includes title, author, publish date, last updated date, summary, and tags.
- FAQ Schema - FAQ schema marks Q&A in a structured way.
- How to Schema - This is a step-by-step process to create schemas. This includes the process, steps, tools, and time required to create schemas.
- Product Schema - Product schema is used for product pages. It helps AI understand the product’s details. Details include the product’s name, price, rating, availability, brand, and images.
- Author Schema - Author schema conveys information (to AI search engines) about the person who wrote the content. This includes the author’s name, bio, credentials, social profile, and the name of the organization.
What Does Schema Do?
Schema helps AI search engines understand the following:
- Who wrote the content?
- When was the content published?
- What does each section mean?
In short, schemas provide AI search engines with a complete roadmap of the content.
7-Step Strategy to Track Content for AI Search Rankings in 2026
As of now, there is no all-in-one solution that helps companies track content performance on AI search engines. Also, tracking content performance on AI search engines is different from performing traditional SEO. It takes a combination of strategies and tools to achieve this goal. Below is a 7-step strategy to track content for AI search engine rankings in 2026.
1. Tracking Citations Across Major LLMs
Whether it's searching on ChatGPT, Perplexity, or Google SGE, they cite the sources whenever they generate content for users. Below are ways to track citations.
- Perplexity Analytics
- Check the sources panel for each query.
- Track the frequency of your domain/website appearing in searches.
- Log recurring topics where the content is cited.
- Monitor competitors who appear in the citations.
- ChatGPT Search
- Use the reference section below the generated answers.
- Check which blogs, articles, or web pages from the company website are displayed.
- Track content topics that get the most citations.
- Google AI Overviews
- Conduct keyword-based and question-based searches.
- Check if the company’s pages appear in the sources list within the overview.
- Track when and why Google downgrades or removes content.
2. Prioritize Visibility Instead of Rankings
Unlike Google search, AI search engines don’t show the position, such as 1 or 2. The secret is to check for visibility in AI-generated answers.
Things to Check in AI-Generated Answers
- Does the AI search engine include the company domain when it provides the answer?
- Is the company content stated as a primary source or a supporting source?
- Does the AI search engine use statistics, frameworks, or definitions (mentioned by the company)?
Manual Testing Techniques
- Test by asking AI questions that users would generally ask.
- Test AI by asking industry-specific questions.
- Ask questions that the company’s target audience may ask.
If the AI search engine uses your content to generate answers, it's a sign that the company’s content is ranking.
3. Monitor Questions Increase Chances of Ranking
AI search engines favor queries that users ask in the form of questions. Examples of question-type queries include the following:
- What is ……?
- What are the steps to …..?
- How does a company achieve ……?
- Best tools to increase ……?
- What are the examples of …..?
- Top 5 strategies to….?
- Step-by-step guide to….
After framing the questions, companies must test them on the following:
- ChatGPT Search
- Gemini
- Perplexity
- Microsoft Copilot
- Google AI Overviews
Does the company website, blog, or webpage appear in these searches? If the answer is yes, the company is heading in the right direction.
4. Measure Brand Mentions Across AI Platforms
One of the strongest parameters to measure AI ranking signals is brand authority. In 2026, companies will need to monitor the following:
- Mentions of the company in AI answers.
- Frequency of AI suggesting the company website as a resource.
- If AI identifies the company as an expert source.
- Whether AI uses the company’s content, including data, to explain complex concepts.
Powerful Tools to Measure Brand Mentions on AI Search Engines
- Perplexity Discover/Trending
- Google Alerts
- Brand 24/Mention
- SEMrush Brand Monitoring
The more the number of mentions, the greater the chance of it appearing in AI-generated answers.
5. Monitor Traffic from AI Search Engines
Yes, AI search engines generate traffic too. Below are some ways to monitor such traffic.
- Check Referral Data
If using Google Analytics or Plausible, check for referrals from the following:
- Perplexity
- Chat.openai.com
- you.com
- Bing Chat Links
- Google AI Preview Links
- Tracking User-Agent Patterns
OpenAI and Perplexity use identifiable crawlers. Monitor server logs for bots such as the following:
- OpenAI-Search
- PerplexityBot
- Google (used for AI crawling)
The more these crawlers access/index the content, the higher its worth for LLMs.
6. Use specialized AI Search Visibility Tools
Below are some of the most potent tools to track AI search visibility.
- Perplexity Analytics - Tracks citation frequency and source usage.
- Open AI Search Dashboard - Checks AI indexing patterns and visibility.
- Neuron Writer - Measures AI content relevance scoring.
- Frase - Checks for LLM-friendliness and clarity.
- Ahrefs - Analyzes backlinks and brand authority.
- Search Console - Measures organic and AI overview impact.
Use the above tools to monitor the following:
- New queries where the company gained greater AI visibility.
- Lost visibility and citations.
- Content freshness signals.
- Competitor visibility.
7. Determining Content’s LLM Friendliness
AI search engines value clear and structured content that conveys authority. Additionally, the content should align with the current times. From the concepts, data, to statistics, everything must be up to date. Some of the best practices for ensuring LLM-friendly content are listed below.
- Content Freshness - Update content monthly or quarterly.
- Readability - Use short paragraphs, along with lists and clear definitions.
- Schema Markup - Apply different schemas, including FAQs, articles, guides, and authors.
- Topic Depth - Large language models prefer in-depth content. They don’t recommend content that just scratches the surface.
AI Search Optimization Techniques for Social Platforms
Previously, traditional search engines only ranked long-form content such as blogs, articles, and webpages. After LLM platforms entered the market, AI search engines use short-form content and recommend it to users. Below are some tips to optimize on social media platforms.
- TikTok - Use clear text overlays and descriptions.
- YouTube - Use comprehensive video descriptions, chapters, and transcripts.
- LinkedIn - Create posts that portray the company as a leader in the industry. The content should have unique insights and display innovation.
- Instagram - Include rich captions, ALT text, keyword bio, and slide text.
5 AI Trends to Watch Out for in 2026 and Beyond
Below are 5 AI trends that companies should watch out for in 2026 and beyond. Understanding these trends will help companies produce content that aligns with AI search engines.
- Increased AI-Generated SERPs
AI-generated results will dominate compared to traditional SEO, where users see links.
- Author Reputation Scoring
Conventional search engines track websites and rank content only. AI search engines track and reward the website plus the author.
- Stronger Focus on Trust Signals
AI will automatically filter AI-generated spam, zero-expertise articles, or outdated information.
- Multimodal Search
AI search engines will analyze more than text. Note that search engines will also consider videos, images, PDFs, documents, screenshots, and more.
- Real-Time Indexing
Search engines can take numerous days or even weeks to index updates. In contrast, AI search engines can index updates in content within minutes or seconds.
Concluding Remarks
As discussed above, AI search engines work differently from traditional SEO. To rank on AI search engines, companies must adopt an innovative approach. This approach includes combining the best SEO practices and implementing strategies to rank on LLM platforms. Even AI values genuine, exhaustive, and unique content.
But that is not enough. The content must be structured properly to get AI’s attention. Only then will it recommend it to users. The tricks and tips mentioned above will help companies step up their game and generate LLM-friendly content. Learn from competitors and how they perform AI search engine optimization.
There is no single best AI search engine. Whether it's Perplexity, ChatGPT, Gemini, or Copilot, all have their pros and cons. Want tips on how to generate the right content that features on AI search engines? Partner with a reputed SEO agency in your country.
