Online search: With AI in the engine, the business model shifts

The evolution of AI-powered search engines is driving a profound transformation in how users access and companies monetize web content. Solutions like ChatGPT Search, Perplexity AI, and Google AI Overview provide concise answers, often eliminating the need to click on external links. This shift is not just a benefit for users; entire industries are being deeply disrupted by the relentless integration of generative AI into online search. For search engines, content creators, and advertisers, the change is radical and requires swift adaptability.

The features of AI-powered search

Advanced search tools integrate natural language processing (NLP) and generative models to deliver conversational, context-aware answers. One example is Perplexity AI, which is picking up momentum, expanding rapidly across desktop and mobile devices. In May 2024, it recorded 67.42 million visits - a 20.71% increase from the previous month. By January 2025, traffic had surged to 132.55 million visits. Financially, Perplexity AI saw a sevenfold escalation in revenue and usage in 2024, fueled by a new $250 million funding round. Many users are beginning to replace Google with Perplexity AI, appreciating its ability to leverage multiple models (GPT-4o, Claude 3 Opus, and Deepseek) and cite sources to enhance accuracy.

In response to the rising popularity of AI-powered search engines like ChatGPT Search and Perplexity AI, Google launched AI Overview, a feature integrated into its search engine that leverages its proprietary AI, Gemini, to optimize information retrieval. AI Overview presents users with AI-generated summaries positioned above the traditional list of external links. Currently, this Google AI tool is available to all US users who meet the minimum age requirement for managing a Google Account, as well as Google Workspace users.

What makes these AI-powered tools so appealing to users? Four fundamental features stand out:

• Natural language integration: Advanced algorithms enhance search engines' understanding of natural language, prioritizing highly relevant content designed to precisely answer user queries.
• Extreme personalization: Search engines are evolving into digital assistants, adapting to each user's specific needs.
• The rise of the “Zero-Click” search: Users receive direct, synthesized answers presented in a conversational format, reducing traffic to original websites.
• Automation: New tools enable multi-step searches that integrate information from multiple sources, benefiting industries like finance and marketing.

Impact on monetization

By 2026, Gartner predicts a 25% decline in traditional search queries in favor of AI-driven solutions. This shift could impact publishers' advertising revenue, as users remain on the search results page rather than clicking external links. Google argues that AI-generated summaries encourage deeper exploration by expanding the variety of sources consulted. However, both advertisers and content creators must rethink their marketing strategies. Positioning within AI-generated answers and ensuring content remains valuable: both these factors will become essential. Meanwhile, Google and Microsoft are experimenting with embedding ads directly into AI-generated responses to protect their margins.

Ethical challenges and misinformation risks

Generative language models sometimes “hallucinate,” presenting inaccurate information as fact. For online search, this raises concerns about the spread of unverified content. Additionally, hyper-personalization and extensive data usage pose privacy challenges. Tech companies are implementing safeguards like source citations, but eliminating errors entirely is still an arduous  undertaking. From a business perspective, reputation management and verification systems are vital, requiring collaboration with reliable sources.

Operative considerations

AI in web search is on the rise, reshaping digital publishing, advertising, and content creation. In this context, companies that integrate digital strategies, information quality, and ethical considerations can gain a competitive advantage. Conversely, underestimating challenges - especially regarding transparency and reliability - could erode market value. Actions to consider include:

• Investing in high-quality content optimized for AI search indexing.
• Exploring advertising opportunities within AI-generated answers and testing new ad formats.
• Implementing fact-checking and third-party verification to mitigate reputational risks.
• Recognizing that competition in this space is rapidly intensifying, which means dedicated resources are needed.