Architectural Intelligence the New Paradigm of Architecture

ALFA – Architecture Papers of the Faculty of Architecture and Design of the Slovak University of Technology , 2021

SUMMARY There is a trend that artificial intelligence (AI) is a direction to take in various scientific disciplines. The idea of ​​AI originated before the 1960s, and with the development of computer technology, the capacities of AI have multiplied. It currently affects many areas of everyday life where we may not even realize that we are already using AI. We are certain that AI is a challenge in the field of architecture and the entire construction industry, where sustainability is one of the current issues. A notable technological shift in the field of building design is BIM. The participants in the process of design are effectively informed about the current state of the project, but the BIM model should be used for further actions, such as utilising information as interactive tool in the construction, operation or renovation phase. The objective of the study is to acquire knowledge about AI usability in the optimization of sustainable design BIM processes in architecture. The aim of the study is knowledge of the applicability of AI in the conceptual solution for reducing the carbon footprint in the BIM model of the building of Faculty of Architecture and Design STU. An assumption for formulating the hypothesis is to use AI to predict the pattern of users’ behaviour. Due to need in the older buildings, where massive refurbishment is not possible or appropriate because of the historical or cultural value. So, it is nearly impossible to meet current requirements for energy-efficient buildings. The article provides a brief overview of AI usability. The base knowledge is presented with terminology in the field of information technology, the processes of artificial intelligence and their applicability to the field of architecture. The context of historical development refers to the considerations of Stanislas Chaillou, who evaluates the connection between the work of an architect and AI as a logical step in technical development. As examples and sources of information studies of application AI in architecture and building industry were used. The study by Stanislas Chaillou is about architecture and AI, where it focuses on the ways and processes of using GAN (Generative Adversarial Network) in floor plan design. The optimization of design processes in BIM is presented by a study that tries to use BIM and artificial intelligence in the design process of buildings. It creates a project called BIMBOT, which generates solutions based on defined priorities for a specific project. The most discussed part of the article is the work of Ekaterina Petrova. Aim of the study is: Integrating knowledge discovery and semantic data modelling for support of evidence-based design decisions. Suggesting a solution to systematization of building design using the BIM-based design, she draws attention to BIM building models, which contain a lot of information that will eventually remain unused. Petrova develops the architecture of a comprehensive software “consultant” system using AI and the cooperation of experts in the field of information technology and the building industry. The result of the study will be a “consultant” which collects information from real buildings throughout their life cycle into a robust database. AI methods are used for re-evaluation and sorting of information to gain new knowledge for sustainable building design processes. The main goal of Petrova research is to transfer the acquired knowledge from real constructions back to the design process, in order to create a connection between relevant factual and data-based knowledge within the initial phase of the design of new buildings. In her work, Petrova also dealt with obtaining specific data from case studies. Based on the statistics, she processed a database of collected information. The data was taken from measurements of two case studies of erected buildings, where she had to find a system categorizing information. The issue of sustainable building designing with AI in the study is proposed from the perspective of the functionality of information technology rather than from the architect’s point of view. The study addresses the challenges of data collection, processing of information in databases and its compatibility. However, this is the point of utilising knowledge, because it clarifies the idea of ​​correct data and outputs when working with a database which consists of many BIM models. A dramatic science fiction for which AI is often taken, may be sometimes true. The article outlines challenges and directions of AI development. Some of them are still unrealistic in the current state of scientific knowledge. However, working with AI itself is advancing in various scientific disciplines, such as medicine and disease diagnosis. AI is currently able to find connections in the data based on statistics of the occurrence of a certain phenomenon. AI is also able to recognize that phenomena. To decide based on abstraction, whether to put phenomena in context, AI is still in its infancy and needs the help of a human expert. AI and humans acquire skills through experience. Some knowledge is very difficult to transform so that AI can “understand” it. If we use AI as a chatbot, it is able to learn concepts based on experience, but does not fully understand the meaning. These issues of working with AI are also transferred to the use in the construction industry or architecture. The article outlines some of these possible problems. Few of them have already been named in studies as specific problems for that case. Other problems are of a general nature or related to the overall development of work with AI. Finally, the study evaluates the potential of working with AI in architecture and ideas about future research. Keywords: architecture, sustainability, artificial intelligence, AI, building information model, BIM, generative adversarial network, GAN

As AI and architecture mediate and control their mutual interactions metaphoric axioms will have cognitive impact on both the future of architecture and AI because there is common metaphor between natural (NI) and artificial intelligence (AI). The inference warrants that for both architectures’ (AI and building) , master builder is an interdisciplinary, multi-crafted and multi-venue team, They are also both arts since they wed intentional ideas to craft and they both make metaphors, the commonality to all the arts. While “architect” actually means master builder and “architecture” the product of the master builder, this is historically identified with habitable buildings. The warrant to the inference of the resolution is that the computer industries (and virtual designers) have made a metaphor referring to the word “architecture” with its conceptual design and fundamental operational structures of computer systems. Already, IT and AI industry metaphorically compare their sciences and art of selecting and interconnecting hardware components to create computers that meet functional, performance and cost goals with the ways and means traditional architects design buildings. There is an interconectivity between the metaphor of computer’s instruction set architecture, or ISA, machine language (or assembly language), Microarchitecture and system design. Theoretically, I warrant that the as the body and mind of AI has identified itself with “architecture” there is an opportunity to use those links to apply and manage risks of AI to building architecture. However, benign, risks include operating system downtime, programming errors, inaccuracy in labeling and dimensions, misreading building codes, local ordinances, misinterpreting FEMA regulations and potential tampering with building security systems. . Further risks include erroneous selection of material and building systems that may expose architects to errors and omissions suits, so many of the general and specific axioms guidelines can be uploaded into the AI architectural system. So with AI potential risk [ff] what can be the impact of artificial intelligence on the future of building architecture?

Energy efficiency and energy preservation are two primary worldwide concerns in current reality. Thus, sustainability encompasses those two issues, giving that as a general term refers to the capacity to endure. In architecture sustainability describes environmentally conscious design techniques, minimizing negative environmental impact and enhancing efficiency in the use of materials, energy and space. In every level of design and construction of a building, environmental issues should be taken into account. Each specific decision and choice may have consequences for the environment. Sustainability through the proper and sound use of materials is an obvious practice. Beyond that, intelligence integrated in buildings can promote energy efficiency and wider life cycle. After a brief clarification of what intelligence in buildings entitles, a series of case studies are presented in order to support the fact that in deed energy efficiency and energy preservation (in some cases energy production as well) are achieved through the use of intelligent systems in structures.

Architectural Intelligence, 2024

Artificial intelligence invades our lives and professions at an ever-increasing pace and intensity. Architecture, engineering, construction, and operation of the real estate have been joining the trend only timidly and belatedly. The paper overviews the basic concepts, methods, general background, and results of artificial intelligence in architecture to date, discusses the achievements and prospects, and concludes the perspectives on the deployment of machine learning in the field. The record of some of the most recent "famous achievements" in the field is set straight and challenged, the flawed idea of a (truly) creative potential of the technology is debunked. Its roots equidistributed both in a farsighted vision of the next workflow of both productive and creative architectural and engineering designing, and construction and real estate management on the one hand and state-of-the-art machine learning on the other, an ambitious though realistic blueprint for R&D of AI-fostered architectural creativity, building design, planning, and operation is tabled for discussion. The attention turns to open-source patterns platforms, generative patterns processing, generative pre-design, parametric evaluation and optimization, latest achievements in machine learning building on reinforcement learning, imitation-based learning, learning a behavior policy from demonstration, and selflearning paradigms zooming in on the design-development processes instead of only on their results. Leveraging the objectivity of assessments and streamlining workflows, artificial intelligence promises to unleash true architectural creativity and leverage the productivity and efficiency of the design, planning, and operation processes.

Open Engineering, 2025

In an era of exponential technological advancement, artificial intelligence (AI) has emerged as a transformative force in architecture, reshaping traditional design and construction practices. This article explores the multifaceted roles of AI in the architectural process, emphasizing its potential to enhance creativity and efficiency while addressing its limitations in capturing multisensory and experiential dimensions of space. Historically, architectural innovation has paralleled technological progress, from basic tools to advanced computer-aided design systems. However, the integration of AI presents unique challenges, requiring architects to critically evaluate its role in design. A narrative review methodology was adopted, focusing on academic sources selected for their relevance, recency, and credibility. The findings reveal that AI is increasingly integrated across various stages of the architectural process, from early conceptualization and site analysis to generative design and construction detailing. AI tools excel at automating repetitive tasks and generating innovative design solutions, freeing architects to focus on creativity and problem-solving. Additionally, AI's (text-toimage) visual representation strength challenges the ocularcentric approaches in architecture, which should push future architects to address the holistic sensory and experiential qualities of space or the critical thinking inherent to architectural design. While AI offers transformative potential, architects must view it as a collaborative partner rather than a passive tool. Integrating AI into design paradigms that prioritize sensory richness, critical thought, and sustainability is essential for creating spaces that resonate on a deeper, more human level. By adopting a balanced relationship between human creativity and AI's computational power, the architectural profession can benefit from this technological opportunity without compromising its core values.

Cihan University , 2026

Why AI is Suddenly Everywhere in Architecture The last decade has seen a convergence of three forces that made AI a practical partner for architects: Driver What it means for design Explosion of data (BIM, IoT sensors, climate databases) Machines can learn from past projects, performance logs, and urban datasets. Advances in generative AI (large language models, diffusion models, reinforcement learning) Designers can ask a system to “imagine” or “optimize” solutions in seconds. Computational design tools (Grasshopper, Rhino, Revit APIs) Seamless pipelines to feed AI-generated geometry or parameters into the design workflow. What used to be a “nice-to-have” computational add-on is now a co-creative partner that can affect every stage of the architectural process—from initial concept to post-occupancy tuning.

Proceedings of the 2012 (3rd) International Conference on Engineering, Project, and Production Management, 2012

There is a serious need for developing an optimized solution of sustainability and intelligence in buildings that will help the agenda of living in a healthy, comfortable, technologically advanced world. A review of the aspects of intelligent buildings and sustainability is presented followed by the study of certain existing projects over the world that incorporates intelligent techniques to achieve sustainability. These concepts were examined through an exploration of the existing literature on impacts of intelligent technologies including scientific literature; government and private organisation reports; and statements from various stakeholders. The research adopts an approach of strategic and critical evaluation of literature to grasp the fundamentals of the current state of knowledge. Outputs from the study highlight the various benefits of intelligent buildings, which include decrease in energy costs, increase in productivity, and investments. Moreover, the comparison of the attributes of intelligent buildings and sustainable practices illustrates the fact that there is a considerable overlap and intelligence can aid greenness. Thus the research concludes that architectural design; green technologies and intelligence in combination may be a pragmatic approach towards the sustainability aspect. Implications from the study also suggest that though intelligent buildings have been a positive impact there is still a wide scope for enhancement.

Proceedings of S.Arch 2020, the 7th international conference on architecture and built environment, 2020

The proliferation of data together with the increase of computing power in the last decade has triggered a new interest in artificial intelligence methods. Machine learning and in particular deep learning techniques, inspired by the topological structure of neurons network in brains, are omnipresent in the IT discourse, and generated new enthusiasms and fears in our society. These methods have already shown great effectiveness in fields far from architecture and have long been exploited in software that we use every day. Many computing libraries are available for anyone with some programming skills and allow them to "train" a neural network based on several types of data. The world of architecture has not remained external to this phenomenon: many researchers are working on the applications of artificial intelligence to architectural design, a few design software allow exploiting machine learning algorithms, and some large architectural firms have begun to experiment with deep learning methods to put into practice data accumulated over years of profession, with a special interest in environmental sustainability and building performance. If on the one hand, these techniques promise great results, on the other we are still in an exploratory phase. It is then necessary, in our opinion, to understand what the roles of this technology could be within the architectural design process, and with which scopes they can facilitate such a complex profession as that of the architect. On this subject we made ten interviews with as many designers and researchers in the AEC industry, In the article we will report a summary of their testimonies, comparing and commenting on the responses of the designers, with the aim of understanding the potentials of using artificial intelligence methods within the design process, report their perceptions on how artificial intelligence techniques can affect the architect's approach to the project, concluding with some reflections on the critical issues identified during the interviews with the designers.

Article, 2024

The swift emergence of artificial intelligence AI underscores its growing significance in shaping the future. Despite the prevalence of AI in various fields such as transportation, healthcare, logistics, finance, and industrial manufacturing, its application in architecture remains relatively uncommon. Nonetheless, a substantial body of research has focused on integrating technological solutions into architectural practices. AI has emerged as a potent tool in sustainable design, reshaping the methodologies employed by architects and designers in building design. This paper presents a descriptive and analytical review of the utilization of artificial intelligence in architecture, specifically aimed at enhancing building performance. The findings of the study point to a growing interest in integrating artificial intelligence within the architectural realm. There is a clear imperative for further research in these areas, leveraging advanced technology and methodologies to advance the integration of artificial intelligence in architectural innovation.

Civil Engineering and Architecture, 2024

The integration of artificial intelligence (AI) in architecture is transforming the design process, making it faster, more efficient, and more sustainable. AI serves as a starting point for conversation, allowing architects to interact with data scientists and engineers. The study recommends merging AI into architecture education to improve designers' comprehension of design-related concepts. The future role of architects in AI design and its application raises questions about how AI design will reflect their creativity and architectural touch. AI is revolutionizing the design process by integrating Building Information Modelling (BIM) techniques and enabling real-time analysis and optimization. It also revolutionizes architectural design education by generating initial project forms and improving interaction with architects. AI applications can revolutionize the way students learn and create, allowing them to explore innovative designs they may not have considered otherwise. As AI applications continue to advance, they have the potential to evolve and provide even more sophisticated design solutions. AI-powered design tools have the potential to revolutionize the way architects approach and create architectural projects. The study explores the potential of artificial intelligence in architectural design. It highlights the integration of AI through generative design algorithms, virtual reality tools, and machine learning algorithms. These tools help architects explore design options, optimize projects for energy efficiency and structural integrity, and analyze large amounts of data for informed decisions. AI-powered design tools can understand aesthetics, architecture schools, and project requirements, enhancing the initial design stage. Integrating Building Information Modeling (BIM) techniques can enable real-time analysis and optimization of designs, saving time and resources. AI applications can also revolutionize architectural design education by generating initial project forms and allowing students to develop innovative designs.