Nyqvist, R; Peltokorpi, A; Lavikka, R and Ainamo, A (2025) Artificial intelligence driven platforms in the construction industry: Implications for companies' business models. Construction Innovation, 25(7), pp. 409-443. ISSN 1471-4175
Abstract
Purpose – This research paper aims to understand the development and impact of artificial intelligence (AI)-driven digital platform business models within the construction industry, addressing their strengths, weaknesses and changes from previous models. Design/methodology/approach – The research uses a three-phase qualitative multiple-case study approach, analyzing three companies developing AI-driven digital platforms. Data was gathered from multiple sources within cases, including interviews, group meetings, workshops and company documentation. The analysis used thematic interpretation of qualitative data and the application of business model canvases for within-case structuring and cross-case synthesis. Findings – Results reveal that AI-driven platforms have potential to enhance collaboration, efficiency and scalability through data-driven, personalized services. Platforms drive new business models and leverage benefits for ecosystem stakeholders. However, adoption faces barriers including high implementation costs, integration complexities, data risks, resistance to change and gaps in stakeholders' maturity. Overcoming the barriers will require strategic planning, training, data governance frameworks, \ and tailored stakeholder engagement. Research limitations/implications – The study acknowledges limitations related to participant bias, partly virtual data collection and regional focus. Future research should expand the sample size and conduct longitudinal studies. Practical implications – The research provides guidance for companies, emphasizing the importance of operational redesign, cultural alignment and training, data governance, collaborative development and fostering ecosystem partnerships. Originality/value – This study contributes to the limited body of empirical research on AI-driven digital platforms in construction, offering insights for companies seeking to leverage platform-based business models in their business.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | artificial intelligence; business models; construction; construction engineering management; construction technology; digitalisation; economics; information systems/management; innovation; it strategies; platforms |
| Index terms: | complexity, construction engineering management, information system, integration, bias, methodology, collaboration, documentation, strategy, face, digitalization, research paper, interview, redesign, artificial intelligence, construction technology, implementation, construction industry, stakeholder engagement, business model, strategic planning, sample size, partnership, case study, workshop, platform, governance, efficiency |
| Subjects: | partnership management, organizational analysis, industry analysis, information systems, systems engineering, management, performance management, probability and distributions, professional development, project management theory and practice, artificial intelligence, data collection methods, business, research design and methodology, community and social dimensions, design methods, research methods, digital design, psychology, digital technology, contractual arrangements, research dissemination and communication, construction type, digital engineering |
| Topics: | Organizational Design, Design Practice, Digital Applications, Stakeholder Management, Construction Technology, Governance, Business Strategy, Research Practice, Information Management, Quality Management, Procurement, Project Management, Engineering Principles |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here