Optimizing for AI Search: Beyond Classic SEO Practices

In an exclusive conversation with Media Infotainment, Vishal Rupani, Co-founder of Sprect.com, shares how brands can thrive in the era of AI-driven search. Rupani explains how optimizing for AI goes beyond traditional SEO, emphasizing content depth, semantic relevance, and structured data to build credibility. He highlights the importance of visibility within AI answers, leveraging schema, knowledge graphs, and voice assistants to stay top-of-mind. Rupani also discusses how generative AI is transforming search into a conversational experience, urging marketers to ensure their brand is confidently referenced across emerging AI-driven platforms.

How does optimizing for AI-driven search differ from traditional SEO practices like keyword targeting and backlink building?

Old-school SEO was a brute force game of quantity over quality. It was all about keyword stuffing and buying links from anywhere you could, because that’s what the early search engines valued. The goal was to trick the system into thinking you were an authority, even if your content wasn’t worth much.

Today, with AI-driven search, the game hasn’t ended; it has just gotten smarter. You are not trying to fool a machine that counts words, you are trying to win the trust of a model that understands context.

So when someone searches for “best pizza in Mumbai”, the AI isn’t impressed by pages that shout the phrase a dozen times. It wants your story. It wants to see if you have the menu, the reviews, even details about the cheese and sauce. It is looking for depth, not noise.

The new jugaad is subtle. You don’t just write an article; you build a complete profile that shows the AI you are the expert. The technical tags and labels might be invisible to readers, but they help the machine piece things together like a detective. The goal is to be so credible and so complete that the AI has no choice but to say, “This is your guy.”

With AI search tools providing direct answers instead of link lists, how can brands ensure visibility and relevance in this new landscape?

AI search flips the visibility game completely. You can have the best content in the world, but if the model answers the question directly, your brand risks becoming invisible. That is why some companies are not just polishing their pages, they are negotiating their way into the machine itself. The Financial Times cut a deal with OpenAI so its reporting appears with attribution inside ChatGPT answers. That is visibility at the source.

For brands that don’t own a newsroom, the playbook is different but no less powerful. HubSpot has been loud about AI Engine Optimization, even launching a free “AEO grader” to check how well your content shows up in ChatGPT, Perplexity, and Gemini.

So what can a brand do? Start by writing content that answers real questions in plain language instead of stuffing keywords. Use schema markup so the machine can easily tag your work. Add simple FAQ or how-to blocks because AI loves that structure. And make sure your name or product appears naturally in the story. The goal is not to chase page one anymore. The goal is to be inside the answer.

Also Read: How Storytelling Campaigns Drive Brand Engagement in 2025

What role do structured data, schema markup, and knowledge graphs play in optimizing content for AI-driven search engines?

Structured data and schema markup may sound technical, but they are basically labels that tell machines what your content really means. Without them, AI has to guess. With them, it knows that a page is a recipe with ingredients and cooking time, or that a profile is about a person with a job title and achievements. That makes the difference between being picked up in an AI summary or being left out.

Knowledge graphs push this one step further. They connect your brand, products, and people into a bigger web of information. If the AI understands that your company sells running shoes, sponsors marathons, and has an athlete as a brand ambassador, it can place you in the right context. That makes your content harder to ignore when someone asks about the best shoes for long-distance runners.

The role of all this is simple. Schema makes your content easy to read, knowledge graphs make it easy to understand. Put them together and you turn your website from a collection of loose pages into a trusted source the AI can confidently quote.

How important is content depth, context, and semantic relevance compared to keyword density when optimizing for AI search?

Keyword density used to be the magic trick. Repeat a phrase often enough and the search engine would assume you were the expert. That does not work in the world of AI search. Models are not counting words. They are scanning for whether your answer actually matches intent. They look at the context around a topic, the way ideas connect, and whether you go beyond surface-level claims.

Depth and semantic relevance matter more because they show authority. A shallow article that repeats “best running shoes” five times will lose to one that explains cushioning, durability, athlete preferences, and even injury prevention. AI is trained to reward detail and meaning. The lesson is simple. Write with the goal of being genuinely useful, not of hitting a keyword quota. That is what gets your content noticed in AI-driven answers.

How can companies drive traffic if AI reduces website clicks?

The uncomfortable truth is that AI search will reduce clicks. People are getting answers right on the results page, which means fewer visits to the original source. I see it in my own behaviour. My daily Google searches are down by almost 90 percent because I now get what I need from ChatGPT or Perplexity. If I am doing it, millions of others are too. That does not mean visibility is gone. If your brand is mentioned inside the AI answer, you are still shaping the decision. In many cases that mention is now as valuable as the click once was.

To keep traffic flowing, brands need to look at new surfaces. Voice assistants like Alexa, Google Assistant, and Siri are becoming mini search engines of their own. If a user says “Alexa, order AAA batteries” and Alexa picks your brand by default, you have won without the website visit. Community spaces and discussion forums matter too. The job now is not only to attract clicks but to make sure your voice is present wherever the AI is doing the talking.

Also Read: Balancing Functional Value with Emotional Storytelling

How do you see generative AI transforming the future of search, and what proactive steps should digital marketers take today to adapt?

Search is heading toward something that looks less like browsing and more like conversation. Instead of ten results and endless scrolling, you will simply ask and get one clear response. That response might come from ChatGPT, Perplexity, or Alexa. It might show up in your car dashboard, your smart TV, or your headphones. Generative AI is turning search into a background layer of daily life, not a separate activity. I hardly “search” anymore in the old sense, because asking an AI is quicker and feels more natural.

Marketers need to plan for that world now. The trick is to stop thinking only about websites and rankings, and start thinking about how your brand can be the voice that gets repeated by these systems. That could mean experimenting with voice assistants like Siri or Alexa, or seeding thoughtful takes on Reddit and Quora where models pick up their signals. The future of search will belong to brands that do not just try to be found, but put themselves in position to be confidently spoken back to the user by the machine.