Digital technologies in the AEC sector: a comparative study of digital competence among industry practitioners

Chen, Xichen; Chang-Richards, Alice; Ling, Florence Yean Yng; Yiu, Tak Wing; Pelosi, Antony; Yang, Nan

doi:10.1080/15623599.2024.2304453

Cited by 2 publications

(3 citation statements)

References 80 publications

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“…The shortage of skilled professionals with expertise in AI, data science, and related fields poses a significant challenge to the widespread adoption of AI in the construction industry [83,112]. Building and deploying AI solutions require specialized knowledge and technical skills, including programming, machine learning, and data analysis.…”

Section: Initial Implementation Costs Data Security and Privacy Conce...mentioning

confidence: 99%

“…Despite these significant benefits, the literature review highlighted several challenges in the application of AI in sustainable building lifecycle. These challenges include initial implementation costs [96][97][98], data security and privacy concerns [62,66,103,104], lack of standardization [105,106,111], skills gap [83,[112][113][114][115][116], interoperability issues [66,[117][118][119], ethical considerations [66,103,120,121], and regulatory compliance [116,[120][121][122][123]. The construction industry's relatively slow adoption of AI can be attributed to factors such as the complexity of construction projects, the traditional nature of the industry, and a lack of awareness or understanding of AI's potential benefits [30,66].…”

Section: Key Findingsmentioning

confidence: 99%

“…Furthermore, the review identified the potential advantages and challenges of integrating AI towards creating a sustainable building lifecycle [20,23,32,47,58,[62][63][64]66,69,70,72,73,83,86,[95][96][97][98][103][104][105][106][111][112][113][114][115][116][117][118][119][120][121][123][124][125]. While highlighting the benefits, such as energy efficiency optimization, predictive maintenance, and waste reduction, the review also addressed challenges like initial implementation costs, data security and privacy concerns, lack of standardization, skills gap, interoperability issues, ethical considerations, and regulatory compliance.…”

Section: Research Contributionsmentioning

confidence: 99%

See 2 more Smart Citations

Application of Artificial Intelligence (AI) in Sustainable Building Lifecycle; A Systematic Literature Review

Adewale,

Ene,

Ogunbayo

et al. 2024

Preprint

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With buildings accounting for a significant portion of global energy consumption and greenhouse gas emissions, the application of artificial intelligence (AI) holds promise for enhancing sustainability in the building lifecycle. This systematic literature review addresses the current understanding of AI's potential to optimize energy efficiency and minimize environmental impact in building design, construction, and operation. A comprehensive literature review and synthesis were conducted to identify AI technologies applicable to sustainable building practices, examine their influence, and analyze the challenges of implementation. The review was guided by a meticulous search strategy utilizing keywords related to AI application in sustainable building design, construction, and operation. The findings reveal AI's capabilities in optimizing energy efficiency through intelligent control systems, enabling predictive maintenance, and aiding design simulation. Advanced machine learning algorithms facilitate data-driven analysis and prediction, while digital twins provide real-time insights for informed decision-making. Furthermore, the review identifies barriers to AI adoption, including cost concerns, data security risks, and challenges in implementation. AI presents a transformative opportunity to enhance sustainability in the built environment, offering innovative solutions for energy optimization and environmentally conscious practices. However, addressing technical and practical challenges will be crucial for the successful integration of AI in sustainable building practices.

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Section: Initial Implementation Costs Data Security and Privacy Conce...mentioning

confidence: 99%

Section: Key Findingsmentioning

confidence: 99%

Section: Research Contributionsmentioning

confidence: 99%

See 1 more Smart Citation

Application of Artificial Intelligence (AI) in Sustainable Building Lifecycle; A Systematic Literature Review

Adewale,

Ene,

Ogunbayo

et al. 2024

Preprint

View full text Add to dashboard Cite

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Digital technology-enabled AEC project management: practical use cases, deployment patterns and emerging trends

Chen,

Chang-Richards,

Ling

et al. 2024

ECAM

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PurposeDespite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This paper aims to discover DT deployment patterns and emerging trends in real-life AEC projects.Design/methodology/approachA case study methodology was adopted, including individual case analyses and comparative multiple-case analyses.FindingsThe results revealed the temporal distribution of DT in practical AEC projects, specific DT products/software, major project types integrated with digital solutions, DT application areas and project stages and associated project performance. Three distinct patterns in DT adoption have been observed, reflecting the evolution of DT applications, the progression from single to multiple DT integration and alignment with emerging industry requirements. The DT adoption behavior in the studied cases has been examined using the technology-organization-environment-human (TOE + H) framework. Further, eight emerging trend streams for future DT adoption were identified, with “leveraging the diverse features of certain mature DT” being a shared recognition of all studied companies.Practical implicationsThis research offers actionable insights for AEC companies, facilitating the development of customized DT implementation roadmaps aligned with organizational needs. Policymakers, industry associations and DT suppliers may leverage these findings for informed decision-making, collaborative educational initiatives and product/service customization.Originality/valueThis research provides empirical evidence of applicable products/software, application areas and project performance. The examination of the TOE + H framework offers a holistic understanding of the collective influences on DT adoption. The identification of emerging trends addresses the evolving demands of the AEC industry in the digital era.

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Digital technologies in the AEC sector: a comparative study of digital competence among industry practitioners

Cited by 2 publications

References 80 publications

Application of Artificial Intelligence (AI) in Sustainable Building Lifecycle; A Systematic Literature Review

Application of Artificial Intelligence (AI) in Sustainable Building Lifecycle; A Systematic Literature Review

Digital technology-enabled AEC project management: practical use cases, deployment patterns and emerging trends

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