Introduction: From Generic AI to Domain-Aware Decision Systems
Shahab Saquib Sohail, Arpita Soni, Satish Mandavalli, Shantanu Kumar, Gautam Siddharth Kashyap · 2026
This chapter analyzes how Artificial Intelligence (AI) has evolved to be more domain-specific instead of a generic, data-driven system of decision making by combining contextual and expert knowledge. The early AI systems, although useful in pattern recognition and prediction, could not process complex information that was domain specific. As the supply of specialized data has increased and the need to make decisions with a high degree of reliability, hybrid methods, which integrate learning algorithms and domain constraints and expert reasoning have developed. This change has been tracked in the chapter, with deep learning and large-scale data processing playing a central role in the development of modern AI. It also notes that domain knowledge is more important in improving interpretability, robustness and reliability especially in high-stakes profession like healthcare, finance and engineering.