The integration of artificial intelligence into architectural engineering is transforming the way buildings are conceived, analyzed, and delivered. Traditionally, engineering workflows have relied on deterministic calculations, human expertise, and sequential decision-making processes. While these approaches remain essential, the increasing complexity of modern projects requires new methodologies capable of processing large volumes of information, evaluating multiple design alternatives, and supporting rapid yet informed decision-making. Cognitive design frameworks have emerged as a response to this challenge by combining engineering knowledge, digital information systems, and AI-driven analytical capabilities within unified decision environments. This article explores the development of cognitive design frameworks and their role in integrating artificial intelligence into architectural engineering workflows. It examines how AI supports design optimization, performance prediction, risk assessment, multidisciplinary coordination, lifecycle planning, and adaptive decision-making. Particular emphasis is placed on the relationship between human expertise and computational intelligence, arguing that future engineering practice will increasingly depend on collaborative decision systems that augment rather than replace professional judgment. The study proposes that cognitive design frameworks represent a significant evolution in engineering methodology, enabling architects and engineers to manage complexity more effectively while improving performance, efficiency, resilience, and long-term asset value.