“Have you ever clicked your mouse HERE? You will.”
That was the text accompanying the first banner ad on the internet, launched by telecommunications company AT&T on HotWired.com in 1994. The ad reportedly clocked a 44% click-through rate in its first four months, a figure that would be extraordinary by the standards of almost any digital marketing channel today.
Over three decades, online advertising has evolved from banner ads to search, social media, programmatic buying, influencer marketing and performance marketing.
Then, with the emergence of search engine optimisation (SEO) practices, brands started optimising websites, building backlinks, targeting keywords and creating content to improve their visibility. Over time, SEO grew into a $90 Bn industry.
But the search box is now changing again.
Today, a growing number of consumers are turning to AI assistants instead of typing keywords into Google and opening a dozen links. Whether they are looking for accounting software, a nearby restaurant or the best smartphone under ₹50,000, they can simply ask an AI assistant for recommendations.
Their interaction with AI is no longer limited to a query or a list of results. Users/consumers ask follow-up questions, compare options, refine their requirements, and direct AI to recommend what they should buy.
This is where answer engine optimisation (AEO) and generative engine optimisation (GEO) have emerged as a new trend. But there is no single platform to optimise for, no standard ranking system and no clear way to measure success.
Much like what the SEO function was in its early days, marketers are still figuring out what works. Agencies are experimenting with how brands appear in answers generated by ChatGPT, Gemini, Perplexity and Google’s AI-powered search products. They are tracking brand mentions, citations and recommendations, while trying to understand why one company gets surfaced over another.
But as brands scramble to show up in AI-generated answers, a bigger question is emerging: How can they ensure they are not just recommended by AI, but show up at the right moment?
The Missing Link In AI Marketing
Currently, for brands, the challenge is not how to appear in AI answers but figure out whether that visibility brings more visitors, customers or sales.
Google historically gave marketers detailed visibility through tools such as Search Console and keyword-level paid search data. This model is considerably harder to replicate when consumers interact with AI through multi-step conversations.
AI platforms currently offer limited visibility into the prompts driving discovery. A user may start with a broad question, ask several follow-ups, compare products, and only then arrive at a purchase decision. For marketers, identifying which interaction influenced that journey is harder than attributing a click to a specific search query.
Organic visibility is also inconsistent across platforms such as ChatGPT, Claude and Perplexity. For queries around the “best” or “top” products and services, AI models may rely heavily on third-party publishers, reviews and user-generated content rather than brand websites.
As a result, brands need to build a consistent information ecosystem across websites, ads, influencers and third-party platforms.
“So, eventually, for optimising, it becomes a lot more important to produce content in the broader ecosystem. We often ask brands to be consistent with their communication,” said Rishabh Mahendru, senior vice president of client success and growth at AdLift.
Marketers are also grappling with how much control they have over their brands’ visibility in AI-driven discovery. AI platforms can answer users’ questions without sending them to an external website. These zero-click answers may be convenient for consumers, but they can reduce traffic to publisher and brand websites.
Even when AI search leads to a sale, tracing that purchase back to a specific interaction can be difficult. A consumer may discover a brand through an AI assistant, research it elsewhere and make a purchase days later. Traditional last-click attribution models may fail to capture the role AI played in that journey.
There is also less certainty around where and how brands appear. AI platforms determine which ads match a user’s intent, while changes in how models cite sources can make organic visibility unpredictable. Brands also risk appearing alongside misinformation, hate speech or polarising content in AI-generated responses. To address these, OpenAI is exploring geo-based ad experiments and brand-suitability pilots to give advertisers more insight into where their ads appear and how they perform.
Overall, with its ChatGPT Ads in India, OpenAI is bringing sponsored messages into conversations on the AI chatbot in one of its largest markets. Ads have been rolled out to users on Free and Go tiers, while Plus, Pro, Business, Enterprise and Education users get an ad-free experience. More than 50 brands were planned to go live during the initial rollout, with WPP and Omnicom as OpenAI’s first agency partners in India. Businesses can access ChatGPT’s self-serve Ads Manager, with daily budgets starting at ₹725.
The Next Frontier Of Brand Visibility
With no standard way to measure AI search visibility or predict which brands will surface in AI-generated answers, startups are building tools to help businesses navigate the new landscape.
Antler-incubated RankinLLM, for instance, is building a GEO and AI search visibility platform. “We operate across three layers: an observability layer to track LLM activity, an intelligence layer to extract meaningful signals from noisy data, and an optimisation layer to fix identified gaps. Optimiser agents create a closed loop, while KPIs such as brand mentions, share of voice, citations and sentiment measure the impact,” said cofounder and CEO Kartik Sharma.
Bengaluru-based TruCommerce has taken a different approach. It initially built a tool to track how often brands appeared in AI-generated answers. But it found that much of the traffic coming from AI platforms was being wrongly counted as direct website visits. This led the startup to shift its focus to helping brands sell directly through AI platforms.
TruCommerce now connects brands’ product catalogues and inventory with AI assistants. This helps businesses track visitors coming from AI, make product information easier for AI tools to understand, and enable customers to buy products without leaving the conversation.
Meanwhile, Lightspeed-backed Gushwork helps small and medium-sized businesses attract potential customers through traditional search engines and AI tools. Its AI agents create content designed to appear in search results, while its platform tracks the enquiries this content generates.
Other startups, including Nexad, Parsnip and AdCreative AI, are also building tools to help brands advertise and improve their visibility across AI platforms.
For marketers, however, this shift is still in its early stages. Traditional SEO took decades to develop its tools, metrics and best practices. AI is at the same crossroads.
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