The discovery and study of exoplanets have made tremendous strides, particularly with the aid of Artificial Intelligence (AI). The surge in data from space missions like Kepler, TESS, and the upcoming James Webb Space Telescope has necessitated the development of automated tools for efficient data processing. Machine learning (ML) and deep learning (DL) algorithms have significantly improved exoplanet detection, identifying planetary signals and refining the analysis of light curves, radial velocities, and other astronomical data. This review traces the evolution of exoplanet detection techniques, from traditional methods to AI-driven approaches, and explores the future of exoplanet exploration using AI.