From Google to AI Search: The Battle for Online Visibility in the Age of Large Language Models

From Google to AI Search: The Battle for Online Visibility in the Age of Large Language Models

Abstract: Search engines are the gateway to online visibility, with businesses competing fiercely for top organic rankings in Google’s search engine to drive customer acquisition. Consequently, Google search engine optimization (SEO) has grown into a billion-dollar industry. Traditionally, SEO has relied on manually written content on companies' web pages to drive organic rankings – an expensive, time-consuming endeavor. This research explores the foundational mechanics of SEO and introduces a semi-automated approach for generating search engine optimized content using cutting-edge natural language generation (NLG) models. Through real-world field experiments in two industries, we demonstrate that AI-generated content not only reduces production costs but also outperforms human-created content – including that of SEO professionals – on key metrics like Google rankings, user behavior, and perceived quality. Yet, as generative AI reshapes content creation, it also disrupts the search ecosystem itself. In the second part of this talk, we examine how generative AI is transforming the dynamics of online visibility. Drawing on an extensive dataset of 200,000 search results from 338 keywords across 36 industries (2019 – 2024), we uncover major shifts in Google’s ranking behavior – especially in vulnerable sectors like services. We also highlight emerging risks: the widespread use of AI-generated content is making web content more homogenous, potentially leading to user fatigue, while AI-powered search engines such as SearchGPT, Google Gemini, and Perplexity increasingly favor large, established brands – amplifying existing market concentration. Taken together this talk offers a comprehensive view of how businesses can leverage generative AI to gain a competitive edge in search visibility, while also navigating the emerging challenges of an AI-driven search environment.

More information on Martin Reisenbichler can be found here.

Please use the following link for Zoom: https://uni-frankfurt.zoom.us/j/62958556058?pwd=b01qWXlrbVMzc1JFVEhjSWNvdGZPQT09