Recent advancements in diagnostic tools have revolutionized the management of benign esophageal diseases, such as gastroesophageal reflux diseaseGERD, achalasia, and Barrett's esophagus (BE). Technologies such as High-Resolution Impedance Manometry (HRIM), Transoral Incisionless Fundoplication (TIF), EndoFLIP, and Volumetric Laser Endomicroscopy (VLE) have significantly enhanced the precision of diagnosing esophageal abnormalities. These innovations allow for real-time visualization and accurate monitoring of esophageal function, leading to more personalized and effective treatments. The integration of artificial intelligence (AI) and machine learning has further improved diagnostic capabilities. AI tools have advanced the detection of dysplasia and neoplasia in esophageal conditions, boosting early detection and diagnostic accuracy. Wide-area transepithelial sampling and tissue pathology systems powered by AI enable the identification of subtle lesions that might otherwise go unnoticed. Additionally, AI-driven algorithms enhance endoscopic imaging, minimizing the risk of missed diagnoses and providing more accurate results. Social determinants of health, such as income, education, and health care access, play a crucial role in the diagnosis, treatment, and outcomes of benign esophageal diseases. Disparities in health care access, particularly in underserved or rural areas, exacerbate health inequities and highlight the need for equitable health care policies. Addressing these disparities can improve early detection and treatment, ensuring that vulnerable populations receive the necessary care. This article will explore 5 key innovations in the management of benign esophageal diseases: HRIM, TIF, EndoFLIP, VLE, and the use of AI in detecting BE. It will also examine how the integration of these technologies has transformed the management of conditions such as achalasia, hiatal hernias, GERD, and BE.