This volume offers an in-depth examination of the expanding role of artificial intelligence and data science in shaping emerging technologies, while also addressing the ethical challenges that accompany rapid innovation. The book integrates methodological foundations with applied research, showcasing advancements in healthcare, agriculture, finance, education, law and cyber security. Drawing on contributions from scholars and practitioners worldwide, each chapter presents unique perspectives, supported by case studies, performance analyses, and model-driven frameworks that illustrate both theoretical and applied significance. Beyond technical exploration, the text underscores the importance of ethical AI adoption by highlighting topics such as fairness, transparency, accountability, and responsible deployment in high-impact domains. Applications ranging from DNA enhancer prediction and market forecasting to intrusion detection, flood risk management, and medical image security demonstrate the breadth and societal relevance of AI solutions. Written for academics, industry professionals, and postgraduate learners, the book delivers actionable knowledge for designing, implementing, and evaluating intelligent systems. Its interdisciplinary scope and forward-looking insights make it an essential reference for research development, curriculum enrichment, and innovation at the intersection of data science, machine learning and ethics.