Evaluating the Efficacy of AI-Driven Models Over Traditional Methods for Enhancing Search Engine Visibility and Website Performance

Artificial Intelligence (AI) has significantly transformed search engine optimization (SEO) by enabling data-driven, adaptive, and predictive optimization strategies. Traditional SEO methods rely heavily on static rules and manual interventions, limiting their effectiveness in dynamic search environments. This study evaluates the efficacy of an AI-driven SEO model compared to traditional SEO techniques in enhancing search engine visibility and website performance. Experiments were conducted on 120 websites across multiple domains over a six-month period. Performance metrics such as organic traffic growth, SERP ranking, click-through rate, bounce rate, and page load time were analyzed. Statistical validation using hypothesis testing confirms that AI-based optimization delivers significant improvements (p < 0.05) across all metrics. The results demonstrate that AI-driven models provide scalable, adaptive, and statistically superior performance, establishing their suitability for modern digital ecosystems.