Brands Have A New Mission: How To Get AI To Say Your Name

Brands are facing a new challenge as consumers increasingly turn to AI assistants for recommendations rather than searching for information. The first banner ad on the internet, launched by AT&T in 1994, had an extraordinary 44% click-through rate, but online advertising has since evolved to include search, social media, programmatic buying, influencer marketing, and performance marketing.

As search engines have become more sophisticated, brands have optimized their websites, built backlinks, targeted keywords, and created content to improve visibility. However, SEO has grown into a $90 billion industry, and now, with the rise of AI assistants, a new trend is emerging: answer engine optimization (AEO) and generative engine optimization (GEO).

Marketers are experimenting with how brands appear in AI-generated answers, tracking brand mentions, citations, and recommendations, but there is no single platform or clear way to measure success. Unlike traditional SEO, AI platforms do not provide a standard ranking system or a reliable method to attribute conversions to specific interactions.

As a result, brands must build a consistent information ecosystem across websites, ads, influencers, and third-party platforms to ensure they appear in AI-generated answers at the right moment.

The challenge lies in determining whether AI visibility translates into increased traffic, customers, or sales. While Google has provided detailed visibility through tools like Search Console and keyword-level paid search data, AI platforms currently offer limited visibility into the prompts driving discovery. AI platforms may rely heavily on third-party publishers, reviews, and user-generated content for queries around the "best" or "top" products and services, making it difficult for brands to control their visibility.

Additionally, AI platforms can answer users' questions without sending them to external websites, which may reduce traffic to publisher and brand websites. Even when AI search leads to a purchase, tracing that purchase back to a specific interaction can be challenging. Traditional last-click attribution models may fail to capture the role AI played in the journey, and brands risk appearing alongside misinformation, hate speech, or polarizing content in AI-generated responses.

To address these challenges, startups like RankinLLM and TruCommerce are developing tools to help brands navigate the new AI-driven discovery landscape. RankinLLM operates across three layers: observability, intelligence, and optimization, tracking LLM activity, extracting meaningful signals from noisy data, and creating a closed loop for optimization.

TruCommerce, on the other hand, focuses on tracking how often brands are mentioned across various platforms, including third-party publishers, reviews, and user-generated content.

As AI becomes increasingly integrated into consumers' purchasing journeys, brands must adapt their strategies to ensure they are not just recommended by AI but also appear at the right moment, driving meaningful engagement and conversions.