AI testing is emerging as a transformative force in software testing, offering significant advantages over traditional automation methods, which are increasingly limited by high maintenance demands and inflexibility. Traditional testing relies on fixed scripts that require constant updates to accommodate changes in applications, creating bottlenecks and high costs. In contrast, AI-native testing employs self-healing tests, natural language processing, and smart test orchestration to adapt automatically to changes, reducing maintenance burdens and technical barriers. The AI testing market is poised for substantial growth, projected to reach $3.8 billion by 2032, driven by its ability to enhance productivity, speed up release cycles, and provide real-time insights into application performance. Enterprises adopting AI testing are realizing competitive advantages through faster releases and reduced costs, as AI platforms not only automate maintenance but also integrate seamlessly with development tools, enabling strategic business intelligence and future-proofing testing infrastructures.