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

Abstract

Artificial Intelligence (AI) has significantly transformed search engine optimization (SEO) by enabling datadriven, 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 AIbased 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.