FROM BARRIERS TO BUSINESS: Analysing AI Adoption in Construction via TOE and DOI, and Building a Consultancy Business Opportunity with Discovery-Driven Planning framework
Author
Varga, Gergely
Term
4. semester
Publication year
2025
Submitted on
2025-06-02
Abstract
Byggeriet er længe bagefter med at tage kunstig intelligens i brug, selv om teknologien kan styrke produktivitet, sikkerhed og beslutningsstøtte. Dette speciale undersøger, hvorfor AI-implementering halter, og hvordan en konsulentforretning kan accelerere digital omstilling, særligt for SMV’er. Et kvalitativt design kombinerer et omfattende litteraturstudie med ekspertinterviews for at kortlægge nuværende anvendelser af AI i fem kategorier (automation/robotik og digital integration, omkostningsestimering og kontraktstyring, datadrevet projektledelse, sikkerhed og risikostyring samt bæredygtighed) og for at identificere barrierer ved hjælp af teorierne Innovationers diffusion (DOI) og Teknologi‑Organisation‑Miljø (TOE). Fundene peger på, at adoptionen befinder sig tidligt i innovationslivscyklussen og hindres af fragmenterede økosystemer, lav digital modenhed (især blandt SMV’er), høje omkostninger ved proprietære løsninger, manglende digitale kompetencer, uklar ROI og svag tværgående samarbejde. Barriererne er derfor både teknologiske, organisatoriske og strategiske. Som svar herpå skitseres en teknologineutral, implementeringsorienteret konsulentmodel, der kan bygge bro mellem bevidsthed og udførelse hos underbetjente SMV’er. Modellen er dog endnu ikke afprøvet, og specialet anbefaler praktiske pilotforløb og kontekstspecifik afprøvning (fx geografisk og fagligt) for at validere og modne konceptet. Bidraget kombinerer innovations- og entreprenørskabsteori med Discovery‑Driven Planning til at udvikle en forretningsmulighed, der kan understøtte en mere inkluderende og bæredygtig digital transformation i byggeriet.
The construction industry has been slow to adopt artificial intelligence despite its potential to improve productivity, safety, and decision-making. This thesis examines why AI implementation lags and how a consultancy model could accelerate digital transformation, particularly for SMEs. A qualitative design combines a comprehensive literature review with expert interviews to map current AI applications into five areas (automation/robotics and digital integration; cost estimation and contract management; data-driven project management; safety and risk management; and sustainability) and to identify barriers using Diffusion of Innovation (DOI) and the Technology–Organization–Environment (TOE) framework. Findings indicate adoption is at an early stage and constrained by fragmented stakeholder ecosystems, low digital maturity (especially among SMEs), high costs of proprietary technologies, limited digital skills, unclear ROI, and weak cross-stakeholder collaboration. These barriers are technological, organizational, and strategic. In response, the study proposes a technology-neutral, implementation-focused consultancy designed to bridge the gap from awareness to execution for underserved SMEs. The model is promising but untested; the thesis recommends real-world pilots and context-specific validation (e.g., by geography and construction segment) to assess viability and scalability. The research contributes by combining innovation management and entrepreneurship perspectives with Discovery-Driven Planning to shape a business opportunity that could support a more inclusive and sustainable digital transformation in construction.
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Keywords
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