Google Search’s market share has fallen below 90% for the first time in almost a decade, according to data from StatCounter. The search giant’s share dipped to 89.34% in the fourth quarter of 2024 before briefly recovering to 90.15% in February 2025. However, it subsequently dropped again to 89.71% the following month and has yet to rebound.
The news was first shared by Mario Nawfal, founder of International Blockchain Consulting Group, on his X account (formerly Twitter), where he commented, “Why dig through link farms when you can just Grok it and get straight to the point?” Elon Musk later reposted this, adding, “AI will obviate search @grok.” This exchange highlights the growing interest in AI-powered search alternatives.
AI search offers several potential advantages over traditional website-based search results. It can provide more convenient and direct answers, cutting through the clutter of SEO-optimized content and sponsored results that often plague conventional search engines. However, AI search is not without its limitations. Instances of AI ‘hallucination’ and incorrect answers have been observed, emphasizing the need for users to verify information through sources.
Moreover, the sustainability of AI search models raises concerns about future commercialization. With AI companies investing heavily in research and development, the likelihood of ad-supported AI search results emerges as a potential revenue stream. The possibility of ‘gamifying’ AI systems also exists, with experts already offering guidance on creating ‘AI-friendly’ content.
The rise of AI search also intersects with ongoing debates about intellectual property and the ethical use of training data. As AI search potentially supplants traditional search methods, addressing these issues will be crucial to maintaining the integrity of AI-driven results and preserving the creativity that underpins AI large language models (LLMs).
Challenges and Considerations for AI Search
While AI search presents opportunities for more streamlined information retrieval, several challenges must be addressed:
- The need for verification of AI-generated answers
- Potential commercialization through advertising
- Risk of ‘gamifying’ AI systems
- Intellectual property concerns related to training data
As the landscape of search technology continues to evolve, navigating these challenges will be essential to realizing the benefits of AI search while maintaining the quality and reliability of information.
