Evaluating AI Integration Maturity in Architectural Practices in the Kurdistan Region, Iraq: A Comparative Benchmark Study

Artificial Intelligence (AI) is being integrated into the architectural profession via processes such as generating images based on design parameters; providing support to help create written descriptions of designs; assisting in the visualisation of buildings before they are built; allowing for greater use of parameters in construction; providing documentation to help complete projects in record time; and assisting in making design decisions. The success of integrating AI into practice depends not only on the use of tools but also on firms’ maturity in integrating AI into their workflows, employees’ capabilities, project teams’ operational efficiency, the impact of investment decisions, and the overall governance of the profession. This research evaluates the maturity of AI integration in architectural practice in the Kurdistan Region of Iraq. To do so, it develops and operationalises the AI Integration Maturity Index (AIMI), an eight-component formative composite index scored 0–37 and organised into five maturity bands (Non-adopter, Exploratory, Occasional, Integrated, and Advanced Strategic). The index comprises adoption, usage, diversity of tools, breadth of workflows, project penetration, staff involvement, training/capacity building, and governance/strategic focus. The AIMI is treated as a literature-derived formative diagnostic tool rather than a universal weighting standard, and was developed through a structured literature synthesis, expert pilot review, and internal-structure validation. Accordingly, its component logic and internal statistics are reported as a transparency and coherence check rather than as reflective reliability claims: Cronbach’s alpha (0.922) is presented descriptively to show component co-movement given the formative specification, while inter-coder reliability (kappa = 0.96) supports the qualitative benchmark coding. The study employs a mixed-methods descriptive comparative methodology consisting of a structured survey instrument administered to 100 architectural firms operating in the local market and structured asynchronous text-based interviews with 10 international architectural firms, comparing the resulting profiles with selected, generally accepted benchmarks and with a sample of leading firms engaged in architectural practice worldwide. On average, total AIMI scores in the local sample were 18.14 out of 37, indicating that local firms are broadly adopting and using AI (82% currently use AI on a regular or occasional basis). By contrast, the international sample yielded a mean AIMI score of 28.60, indicating that local firms exhibit a significantly lower level of maturity than the international benchmark, with the largest gaps in staff involvement, project penetration, and overall engagement with AI use. The paper concludes that the primary challenge facing architectural firms in the Kurdistan Region is no longer basic awareness or technological infrastructure, but rather the transition from broad and superficial AI adoption to a systematic, structured, project-based, and well-governed integration of AI within the architectural profession.