Artificial intelligence and its role in accelerating decision-making processes in architectural design.

Architectural design has come a long way from hand-drawn blueprints and physical models to the digital age. The integration of artificial intelligence into architectural design has revolutionized architectural and building designs. It contributed to saving effort and time. It depends on processing data and inputs at a high speed that allows expansion of the visual base for designers, as big data analytics is the process of searching huge data sets for patterns, trends, relationships, etc. These complex analyses require specific tools, techniques, and significant computing power. With the increase in computational techniques used for architectural purposes, these techniques provide many designs, proposals, and presentation methods, provide appropriate solutions as quickly as possible, obtain fast and accurate analysis and modeling data, and prepare and modify proposals easily. Through the use of visualization and modeling techniques, it can provide accurate guidance based on complex analyses, reducing the time needed to make engineering and design decisions. It also can efficiently and inexpensively create projects to test before actually building them. Computational techniques used for architectural purposes are increasing, so not using artificial intelligence in making architectural design decisions may lead to missing opportunities to improve efficiency and improve interaction between architectural elements. Problems can arise in analyzing big data to use it to make smarter decisions, and this may lead to designs that are ineffective or less suited to the needs of users and the environment. Therefore, data-based systems should be developed rapidly to adapt to the huge amount of documentation data that will be generated as a result of the construction process, taking into account the complexity of the architectural design process. The paper examines the impact of making architectural design a process of data processing to reach the best possible computing results and its role in the design decision-making process.