Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder that affects both children and adults, is characterized by symptoms of inattention, hyperactivity, and impulsivity. Globally, ADHD affects approximately 5-7% of children and adolescents, as well as 2.5% of adults. The condition significantly impacts daily functioning, social relationships or interactions, and academic or professional performance. ADHD appears differently in different age groups, with classroom disruptions and difficulty in social interactions being common in children, while adults may struggle with time management, organizing, and maintaining interpersonal connections. The disorder is categorized into three main types: mainly inattentive, mostly hyperactive-impulsive, and combination presentation, which are defined by dominant symptom patterns. Diagnosis involves ongoing symptom assessment, with treatment options including medications, behavioural therapies, and management strategies tailored to individual needs. The growing use of Artificial Intelligence (AI) in healthcare has significantly improved ADHD diagnosis and treatment, offering higher precision, efficiency, and personalization. AI algorithms enhance diagnostic accuracy by analyzing large datasets and identifying complex patterns in medical images, enabling early detection of ADHD and related conditions. Moreover, AI-driven treatment plans personalize therapeutic techniques based on individual patient data, improving outcomes and reducing adverse side effects. Benefits of AI include improved diagnostic accuracy, increased efficiency through automation, development of personalized medicine, and reduced healthcare costs. This review explores the role of AI in ADHD diagnosis and treatment, focusing on its transformative potential in improving patient care and advancing precision medicine. Understanding AI applications in healthcare can lead to way for more effective ADHD therapy management and improved patient quality of life.