Developing an Artificial Intelligence Maturity Model (AIMM) applicable to UK construction industry

Hamza, Ummul-yumn

Abstract

Despite the wide adoption of Artificial Intelligence (AI) in many sectors, like the construction industry, there is a significant concern that many organisations within the construction sector lack an objective approach to adopt and implement AI in their processes. As a result, this study proposes a robust Artificial Intelligence Maturity Model (AIMM-CI) designed with the capability of evaluating and determining the level of AI technology adoption and implementation in UK construction companies. The model was built on the foundation of the Peffers framework, extensive literature review, empirical insights, and stakeholder perspectives, thereby making it a tailored model specifically designed for the unique challenges and opportunities present in the UK construction industry. Through a meticulous exploration of the existing AI technologies, both in the construction industry and a comparative study with other industries, the study drew insights from diverse use cases, identified parallels, contrasts, and unique challenges in relation to AI adoption. More so, both quantitative and qualitative analyses were conducted to capture the perspectives of expert stakeholders directly involved in the UK construction industry. By using this systematic approach, a total of seven (7) themes were identified as the key factors that influence the adoption of AI in the UK construction industry. These seven (7) themes include Data Availability and Usability, Organisational culture, Human Capital Development, Robust Business Case, Legal Regulations, Stakeholder’s Support, and Technology and Tools. The seven (7) themes contained a total of 40 success factors: Data availability and usability contained 5 success factors; Organisational culture contained 7; Human capital development contained 6; Stakeholders' support contained 5; Legal regulations contained 4; Robust business care contained 9, and Technology and tools contained 4 success factors. The seven (7) themes and the 40 success factors formed the framework used in designing the AIMM-CI model. The AIMM-CI model comprise seven dimensions; each dimension is intricately linked to the overall maturity of AI adoption. The model provides a systematic approach for construction companies in the UK to evaluate their AI adoption current state, identify areas for improvement, and progress through maturity levels. Therefore, the AIMM-CI is not just a theoretical construct; it is a practical tool that construction companies in the UK can leverage to navigate the complex terrain of AI adoption. It holds profound implications for the UK construction industry, as it offers practical insights and guidance for companies seeking to adopt and mature their AI capabilities. In essence, when organisations strategically address data challenges, cultivate a collaborative and innovative culture, optimise technology readiness, develop robust business cases, manage stakeholders effectively, and navigate legal and ethical dimensions, they position themselves for comprehensive AI maturity.

• Thesis Type: Thesis
• Deposit Date: Jan 25, 2024
• Publicly Available Date: Oct 16, 2024
• Public URL: https://uwe-repository.worktribe.com/output/11627971
• Award Date: Oct 16, 2024