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Closing the AI divide: a practical blueprint for construction SMEs
Paul McGrady Site manager, GEDA Construction
Image: Atcharapun Samorn | Dreamstime.com
Construction SMEs must be part of the wider industry’s AI journey, but how can they get on board? Paul McGrady, a site manager at County Tyrone-based GEDA Construction, has researched the issue as part of his MSc in Construction Project Management. Here he details the challenge and proposes solutions.
More than 90% of construction firms in the UK and Ireland are SMEs, yet most are not ready for AI. If this continues, the industry’s digital future will be built on a fault line.
Large contractors are already embedding AI in project scheduling, safety monitoring and design optimisation. But many smaller firms still lack the systems, skills and investment to keep up.
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Unless this gap is closed, the sector risks creating a two-tier industry: one digitally advanced, the other left behind. AI is no longer a futuristic concept for construction. From predicting project delays to monitoring safety through computer vision, AI is transforming productivity, reducing risks and improving decision-making.
Global market analysis projects that AI in the construction sector will grow from $1.8bn to $12.1bn by 2030. But behind this potential lies a critical problem: the majority of firms in our industry – small and medium-sized enterprises (SMEs) – are at risk of being left behind.
My recent University of Portsmouth research, surveying 156 professionals across the UK and Ireland, reveals a significant digital divide. While large contractors are advancing rapidly, most SMEs face structural barriers that limit adoption. Unless these challenges are addressed, this divide will widen, threatening the competitiveness and sustainability of the vast majority of the sector.
SMEs – the backbone of construction
“The construction sector cannot afford to let SMEs fall behind. If the vast majority of firms are excluded from AI-driven productivity gains, the whole industry’s performance will suffer.”
Paul McGrady
SMEs deliver the bulk of subcontracted work, specialist trades and regional projects in the UK and Ireland. Their agility and entrepreneurial spirit are undeniable strengths, but they also face persistent resource constraints that create a unique adoption landscape:
financial - smaller budgets and limited access to credit make it difficult to fund speculative technology investments;
people - SMEs rarely have dedicated digital teams or the capacity to release staff for extended training; and
organisational - flat hierarchies and owner-manager decision-making mean digital strategies are often informal or absent, lacking the structured approaches of larger firms.
These characteristics mean that the enterprise-wide rollouts common in large firms are rarely feasible for SMEs.
What the research revealed
The study used a comprehensive readiness framework (Technology, Organisation, Workforce, Leadership, and Environment - TOWLE) to benchmark SMEs against large firms. The results were stark:
large firms consistently outperformed SMEs across all five dimensions of AI readiness;
the most significant gaps were in organisational readiness (e.g., strategic roadmaps, budgets) and workforce skills; and
a notable finding was that SMEs showed relative strength in cultural adaptability, they are open to change and new ways of working. However, this willingness cannot compensate for deficits in technology and skills.
The barriers holding SMEs back
The research identified the most critical barriers for SMEs, with the top three being:
High implementation costs - the initial investment in software, infrastructure and integration is a major hurdle, with an uncertain return on investment deterring cashflow-sensitive SMEs.
Lack of in-house expertise - a shortage of digital skills makes it difficult to evaluate, procure and implement AI solutions effectively.
Limited IT infrastructure - fragmented systems, poor data quality and weak data governance create a poor foundation for integrating AI tools.
These barriers are not new, but the rise of AI makes them more urgent. Without a foundation of skills and infrastructure, SMEs risk permanent exclusion from the benefits of digitalisation.
The pathway to success: critical enablers
Despite the challenges, the research identified clear enablers for AI adoption in SMEs. The most important were:
Strong leadership commitment - when owners and senior managers champion digital innovation and allocate resources, adoption becomes possible.
Workforce training and upskilling - practical, targeted training allows existing staff to engage with AI without overwhelming their core duties.
External partnerships and collaboration - SMEs benefit immensely from working with technology providers, consultants and universities to access expertise and share risks.
A clear, phased strategic roadmap - starting with small, well-defined pilot projects helps SMEs build confidence, demonstrate value and learn before scaling up.
In short, AI adoption is not out of reach for SMEs, but it requires a tailored, incremental pathway distinct from that of large corporations.
Why this matters for the entire industry
The construction sector cannot afford to let SMEs fall behind. If the vast majority of firms are excluded from AI-driven productivity gains, the whole industry's performance and innovation potential will suffer. Supply chain inefficiencies will persist, and collaborative digital delivery models will be hampered.
This is not just about competitiveness – it is about fairness and resilience. The digital divide threatens to create a two-tier industry. Bridging this gap is essential for a more productive, innovative, and inclusive construction sector.
A call to action: what needs to change
Based on the research, coordinated action is needed across three levels:
For SME leaders:
think incremental - start with practical pilots in high-impact areas like AI-driven cost estimation or safety compliance.
leverage your agility - use your cultural adaptability to your advantage. Encourage staff experimentation and feedback; and
view SME capability as supply chain resilience - investing in your subcontractors’ digital maturity benefits your own projects through better integration and data flow; and
foster mentorship and partnerships - lead joint initiatives, share knowledge and create onboarding support for SME partners.
For policymakers and institutions:
provide targeted incentives - introduce grants, subsidies or tax relief specifically for digital adoption in SMEs;
support accessible training - fund sector-specific, practical digital skills programmes that are feasible for time-poor SME staff; and
build collaborative ecosystems - support innovation hubs that connect SMEs, technology providers and academia.
A strategic necessity
AI promises to transform construction, but the benefits will only be fully realised if SMEs – the backbone of the industry – are brought along on the journey. My research shows that while SMEs are open to innovation, they face unique challenges that demand tailored strategies and targeted support.
Closing the digital divide is not optional. It is a strategic necessity for an industry that aims to be competitive, sustainable and attractive to future talent. SMEs cannot be left behind. With the right leadership, partnerships and policy frameworks, they won’t be.
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