OptimizeGEO CEO Kirthiga Reddy on AI Search, Brand Visibility and the Future of GEO

1)  OptimizeGEO recently surpassed 100 global brand clients across 20 countries, with Michael Kassan joining as an investor and strategic advisor. What is driving this momentum, and what does it tell you about how enterprise marketers are prioritizing GEO?

Market share is won and lost at moments of technology disruption. I saw it at Facebook with the shift to social and mobile, and we are in the next big consumer shift now. People are no longer searching for links. They ask ChatGPT, Gemini or Perplexity everything from which moisturizer to buy to which software to choose, and they get two or three recommendations back. Intent is formed before anyone visits a website.
That is what is driving the momentum. We now work with more than 100 brands across 20 countries, from Fortune 1000 companies to high growth startups, and the CMOs among them have realized this is not a channel you bolt on at the end. It cannot be the seasoning you sprinkle on after the fries are made. It has to be an ingredient in how they are made, because AI reflects everything said about you, across your site, content, PR, creators and media.
It also tells you where GEO now sits. It has moved from the SEO team to the boardroom. Leaders are asking about their share of voice inside AI answers, who owns it, and how fast they can act. Gartner found 70% of CMOs want to be AI leaders this year, but only 30% have the infrastructure to get there. The window to experiment used to be a year or two. Now it is three to six months.
Michael Kassan has an instinct for category creation, and his backing reflects where this market is heading. For challenger brands, this is the moment to leapfrog. For incumbents, it is time to act like a challenger.

 
2)  Zero-click search and AI-generated answers are fundamentally reshaping discovery and how to compete for consumer attention.  What does it take to become one of the brands AI consistently recommends? What are the business risks for competitive share?

Nearly 75% of shoppers now use AI for search, discovery and recommendations, according to NielsenIQ. We have moved from an attention economy to a trust economy. The question is no longer how many clicks you earn. It is whether AI trusts your claims enough to recommend you.
People call AI search a BS detector, and they are right. If your website says your product is the best for sensitive skin, but creators, reviews and user surveys say something different, AI will not recommend you. The brands AI recommends consistently have clarity, consistency and credible independent sources backing what they say.
Most of that evidence lives off your website. In our analysis of 40,000 unbranded shopping queries across 12 consumer categories, editorial publishers made up 72% of the sources AI cited. Brand websites accounted for about one in seven.
The business risk is that share moves without anyone seeing it. A shopper asks, gets two or three names and decides. If you are not part of those answers, you are forgotten by the modern consumer. Fame does not protect you either. We saw a leading consumer goods brand go missing from 43% of the questions where its competitors were recommended.

 
3)  How should marketers be thinking beyond visibility, and how is OptimizeGEO helping brands turn intelligence into meaningful action and business outcomes? 

Visibility tells you that you showed up. It does not tell you whether you were recommended, to which customer, at which moment, or whether it led to a sale. The better question is demand: who is asking, what are they trying to decide, and which brands is AI pointing them toward.

That is what our Integrated Demand Engine is built to answer. Persona Intelligence builds custom audience personas for each brand and generates the questions those people ask, so visibility, share of voice, sentiment and citations are measured against real customers rather than a generic keyword list. Cross Channel Optimization turns that into prioritized recommendations across owned, earned and paid media, including how products show up on the AI shopping shelf. Agent and expert led execution then gets the work done, with technical, content and off site agents producing fixes that are ready to deploy and a person approving every change.

On top of the engine, we have just added AI Ads Insights, AI Shopping Intelligence and Execution Agents. The outcome we hold ourselves to is qualified traffic, consideration and revenue, not mentions.

 
4)    What does OptimizeGEO do differently that a brand can't get from a generic AI-visibility dashboard? 

Dashboards tell you whether you appeared. Enterprise leaders need answers a dashboard cannot give them: which customers are we losing, why and what will change it.

The first difference is who we measure for. Most tools run a generic list of prompts. We start with a brand's actual customers, whether that is a first time parent, a value shopper or someone with sensitive skin, and the questions each of them asks AI. That is where the blind spots sit. In one skincare diagnostic, a brand held 43% share of voice overall but was invisible on 40% of safety related questions. The headline number looked healthy. The decision moments did not.

 The second is the full picture. AI discovery now spans organic answers, paid placements and shopping results. We put all three side by side, with the sources behind each answer, so a CMO can decide where to earn a recommendation and where to pay for presence.

 The third is action. Insight without execution is where most enterprise programs stall. We rank recommendations by business impact, and our agents and strategists deliver the work across content, site, retail, creators and PR, with the brand approving every change. Success is not a better report. It is a stronger position in the answers that drive revenue.

 
5) How do language, geography and cultural nuances influence which brands AI platforms recommend? What are the risks for global marketers who approach GEO with an English-first or U.S.-centric strategy? 

AI answers are local, even when the brand is global. Ask the same question in another language or another market and the shortlist changes, and so do the sources behind it: local publishers, local retailers, local reviews.

This is not a niche issue. OpenAI has said that more than half of active ChatGPT users now mainly use a language other than English. That is why we built OptimizeGEO to work across languages and markets from day one. Shopping shows it clearly, because the AI assistant that matters in the US is different from the one that matters in Japan or Singapore, and each has its own rules about who gets seen.

 The risk of an English first strategy is treating translation as localization. A brand can lead in English and barely appear in another language, because the evidence AI relies on there is thin or out of date. That applies inside the US as well, where millions of shoppers ask in Spanish and other languages. If your GEO plan only checks English prompts, you are blind to part of your own market.

 
6)   What is the first step for brands to do to start a GEO strategy and what is the biggest mistake you see brands making when they do start?

Start by understanding where you stand. Define the few personas that drive your business, find the questions each of them asks AI when choosing in your category, and measure your position across every major engine. Most brands are surprised by the first baseline.

 The biggest mistake is treating AI visibility as a vanity metric. A brand can hold the number one spot on awareness questions and drop off entirely on the consideration and decision questions where purchases happen. Look at where you show up across the journey, not just the headline score.

 The second mistake is assuming the fix is your website. In our analysis, editorial publishers made up 72% of the sources AI cited for shopping questions, and brand sites about one in seven. AI does not see your org chart. It sees one body of evidence. Marketing should own the outcome, but PR, content, commerce, creators and product all shape what AI reads.

7)  Can you share an example of how a brand used insights from OptimizeGEO to uncover a competitive blind spot or growth opportunity? What actions did the company take, and what measurable results followed?

Glance is a good example. It is a pioneer in AI agentic commerce, working with leading retail and fashion brands and reaching millions of users worldwide. Yet when people asked AI shopping questions in its category, Glance was close to invisible. Reach was never the problem. Being recommended was.

 We did not chase an overall score. We started with the shoppers Glance wanted to reach and the questions they were asking, such as how Glance differs from Amazon's shopping assistant, or how it creates outfit looks on a real body. Then we built the answers engine by engine, because each engine behaves differently. Four questions drove 62% of the gain.

From April to July 2026, Glance's AI visibility grew 2.5X and its share of voice in the AI shopping category grew 6.6X. In a category where most leaders were declining, it was one of the few closing the gap.

8) How should marketing teams be rethinking attribution now that AI answers sit directly between a brand and the consumer? Which metrics matter most beyond mentions, citations and share of voice?

First, stop blending. Track paid, organic and cited sources separately, and look at them persona by persona. A brand that wins with one type of customer and disappears for another needs to know that, and a single blended number hides it.

Second, separate being mentioned from being recommended. Appearing somewhere in a list of ten brands is very different from AI saying, this is the one I would pick for you. Most reports count both as a mention, which makes the numbers look better than the reality.

The metrics I care about most are recommendation rate in decision moments, meaning comparison, price and safety questions rather than broad category questions; accuracy, meaning whether AI describes your product, price and claims correctly; and source share, meaning which publishers, retailers and reviewers shape the answer. Then connect it to the business. That is why we integrate with GA4, so teams can see AI referral traffic, branded search and conversion for the questions they have moved, in the analytics they already use.

The aim is not perfect attribution. It is knowing which answers you are winning and whether winning them changes revenue.

9)  How do you see GEO evolving as AI assistants become more integrated into shopping, product recommendations and commerce? What should brands be doing now to prepare for that future?

GEO and commerce are merging. McKinsey estimates AI agents could orchestrate $3 trillion to $5 trillion in global consumer commerce by 2030. When the assistant picks the product, GEO stops being a marketing metric and becomes a sales channel.

That means competing at the product level, not just the brand level. A brand can look strong overall while its bestselling product is missing from the AI shelf. Our AI Shopping Intelligence tracks individual products across AI shopping platforms, showing which products get recommended, how they compare with competitors and which retailers capture the demand.

To prepare, fix what an agent will rely on: specs, price, availability, delivery and returns. Treat retailer listings as part of your GEO strategy, because three out of four AI shopping shelves in our analysis sent shoppers to retailers. Pilot agent led buying in low risk, repeat purchase categories first. And keep building a direct relationship with your customers that does not depend on any single AI sale.

10) If a brand pays for an AI ad, does it change what the AI recommends organically?

No, and marketers need to plan around that. OpenAI says ChatGPT ads sit below the answer, are clearly labeled and do not change what the answer says.

So a brand can pay to appear next to an answer it is not in. It can run an ad under a comparison where a competitor is recommended, or beside outdated information about its own product. Paid gets you near the conversation. It does not fix what the answer gets wrong.

This is now a real channel. ChatGPT ads have passed $1 billion in annualized revenue. That is why we built AI Ads Insights, which shows which brands are advertising on which prompts and with what creative, and puts paid share of voice next to organic visibility. The smart move is to use paid where organic is weak and will take time to earn, and to stop paying for ground you already win.