The concept of artificial intelligence (AI) has become a paradigm shift in the field of cognitive disease diagnosis and has altered the manner in which neurological diseases like Alzheimer, Parkinson, and dementia are identified, monitored and interpreted. Chapter discusses the dynamic healthcare of cognitive in a multidisciplinary perspective, including technical progress of machine learning, multimodal analytics, neuroimaging, speech processing, and digital biomarkers. The AI tools have boosted the rate of rapid finding promptly to improve diagnostic precision and individualized treatment setup. Nevertheless, the generalizability of AI in research settings to daily clinical work is still criticized because of the doubts of diversity in the data, bias in the algorithm, within-model explanability, regulation preparation and corresponding ethical responsibility. Using the latest research studies and the world health views, the chapter assesses the possibilities and constraints of AI as a clinical decision-support companion instead of the human expertise substitute. It also examines world governance structures, human-AI relations and the growing demand of transparency, interpretability and reliability of AI systems. The chapter also looks to a vision of the roadmap of the future, which is based on predictive and preventive modeling, digital twins, distributed data, integrative computational technologies, and human-centered design. However, it is up to all of us to align technological innovation with moral responsibility, non-invasive data practices, regulatory convergence, and long-term human-AI symbiosis that improves, rather than substitutes, clinical judgment and humanistic care that determines the future of AI in the field of cognitive healthcare.