
Ce travail de recherche et sa mise en place découlent du constat d’un manque de données concernant l’appropriation et la mise en place des outils d’IA générative au sein des agences d’architecture. Ainsi, ce stage a été réalisé en alternant présences au laboratoire de recherche MAP-CRAI (ENSA Nancy) et Metaform Architects (Luxembourg), une agence internationale de plus de 60 employés travaillant sur des projets de grande envergure.L’objectif de cette recherche est d’analyser les usages concrets de l’IA générative en agence, d’identifier les freins et opportunités, et de proposer un cadre structurant adapté à l’agence.La première phase d’alternance de ce stage a débuté au MAP-CRAI par une période d’analyse et de recherche sur la littérature et les pratiques actuelles (figure 1 - Livrable 1) afin de, par la suite, les confronter avec la réalité d’une agence telle que Metaform au travers d’analyses, observations, entretiens semi-directifs et expérimentations (figure 1 - Livrable 2). L’objectif est de clairement définir la manière dont l’agence s’est saisie jusqu’alors de cette technologie et d’identifier clairement les besoins et attentes vis-à-vis de celle-ci (figure 1 - Livrable 3).
This research work and its implementation stem from the observation of a lack of data regarding the adoption and integration of generative AI tools within architecture firms. Consequently, this internship was carried out by alternating between time spent at the MAP-CRAI research laboratory (Architecture school of Nancy) and at Metaform Architects (Luxembourg), an international firm with more than 60 employees working on large-scale projects.The objective of this research is to analyze the concrete uses of generative AI within architectural practice to identify obstacles and opportunities, and to propose a structuring framework adapted to the firm.The first phase of this internship began at MAP-CRAI with a period of analysis and research on the literature and current practices (Figure 1 – Deliverable 1), with the aim of later confronting them with the reality of a firm such as Metaform through analyses, observations, semi-structured interviews, and experiments (Figure 1 – Deliverable 2). The goal is to clearly define how the firm has so far engaged with this technology and to clearly identify its needs and expectations with respect to it (Figure 1 – Deliverable 3).
Intelligence Artificielle, Agences d'architecture, Innovation adoption and diffusion, [INFO.INFO-ET] Computer Science [cs]/Emerging Technologies [cs.ET], [SHS.ARCHI] Humanities and Social Sciences/Architecture, space management
Intelligence Artificielle, Agences d'architecture, Innovation adoption and diffusion, [INFO.INFO-ET] Computer Science [cs]/Emerging Technologies [cs.ET], [SHS.ARCHI] Humanities and Social Sciences/Architecture, space management
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
