AI is transforming everything. But high on the hitlist is a fundamental overhaul of how search performance is measured. With AI overviews and LLM-generated answers giving users the info they need directly in search results, clicks and traffic alone no longer capture true impact, says VML.

In this new iteration of search, brands may influence perception and purchasing decisions without ever earning a click, making visibility within AI answers increasingly critical. Success increasingly depends on how often brands are seen and trusted in AI answers, and how well that visibility translates into meaningful business outcomes, adds VML.

Traffic-Based Reporting is Out

AI is compressing search journeys and redefining what performance looks like. For two decades, users would type a few keywords into a search bar and navigate the list of URLs the search engine returned like browsing ads for electricians in the Yellow Pages, says VML.

For brands, the goal was simple: be featured on page one, as high up as possible. You could buy your spot or follow the rules of SEO and stand a good chance of earning it. You knew your strategy was successful by how many clicks you got, adds VML.

In AI search, that metric of success is no longer as reliable as it once was. Brands must expand beyond traffic-based reporting and adopt a visibility and revenue framework that reflects how discovery and influence now happen across AI platforms, traditional search results, social media properties and more, says VML.

The New KPIs of Search

VML's 2026 AI Search Report aims to identify trends in how people are using search and how brands can best adapt. 

On the optimisation front, that means thinking beyond an individuals own website to how they can manage their brand's narrative across the entire digital ecosystem. Every piece of content (including text, video and product data) should be meticulously structured to become the definitive source that AI systems choose to feature and cite. That extends beyond owned channels to forums, review sites and media outlets, says VML.

The goal is to appeal to AI for discovery and humans for conversion.

It's a work-intensive process that involves layering GEO (Generative Engine Optimisation) on top of existing SEO (search engine optimisation) and it extends to the entire web. So brands will naturally want to know whether they're getting a worthwhile return on the time, effort and budget spent. The report identifies four ways to adjust search KPIs for the AI era, says VML.

Supplement Traditional KPIs With AI-Centered Visibility Metrics

This involves tracking metrics such as brand citations, mentions, and sentiment across multiple AI platforms. Brands that focus only on ChatGPT, for example, could be missing out on key data from other models like Copilot, Gemini and Claude, says VLM.

Prioritise Building Trust and Expertise

 Build authority and trust through expert-driven content, structured data and original insights that earn credible mentions and citations. This includes content on owned channels, such as your brand's website and social media, as well as external sources, such as media interviews and Google reviews, says VML.

Share of Voice (SOV) may serve as a metric for how well your brand is showing up outside of an individuals own environment. Requesting reviews that rate specific parts of the customer experience reveals where brands are excelling and where they can improve, adds VML.

Develop a Framework to Track the Broader Impact of Discoverability Efforts, Not Just Site Traffic

That includes measuring things such as engaged sessions and organic search-assisted conversions. The report found that modern users adopt a multi-tool approach to search. Even as AI search rises, Google's search volume has not dropped, suggesting that users are leveraging AI for certain tasks and still relying on traditional search for others, says VML.

Add Cross-Channel Inputs to Any Discoverability Measurement Strategy

Any useful measurement strategy for 2026 should include inputs that consider the impact of community forums, social media content and third-party publishers, which all contribute to a brand's SOV, says VML.

Search has always rewarded brands that adapt. Two decades ago, Google made businesses without a web presence increasingly difficult to find. Today, the same principle applies to AI search. Brands that fail to adapt risk becoming less visible at the very moment customers are looking for answers, adds VML.

Download the full VML 2026 AI Search Trends report here.

For more information, visit www.vml.com. You can also follow VML on Facebook, LinkedIn, X, Instagram, or on TikTok. 

*Image courtesy of Facebook