Global Digital Construction Outlook 2024
Benefits and risks
As companies throughout the construction supply chain adopt digital tools and AI, stakeholders need to carefully evaluate both the potential benefits and associated risks.
Benefits
All our office leads viewed enhanced efficiency and productivity as the primary benefits of digital transformation and AI in construction. They also recognised that increased use of technology leads to more informed decision-making, accelerates project delivery and improves quality.
Increased efficiency and productivity
Investing in digital tools and high-quality data can help to make the best use of resources and improve efficiency and outcomes.
The adoption of technology can improve efficiency across the entire project lifecycle, enabling optimal resource allocation.
Better decision-making
Analysing information such as historical data and current market trends allows AI algorithms to identify patterns and trends, enabling construction teams to make well-informed choices based on data-led insights rather than relying on intuition or limited personal experience.
The "Uniqueness Bias: Why It Matters, How to Curb It" report by Bent Flyvbjerg, Alexander Budzier and M.D. Christodoulou highlights how project managers often view their projects as entirely unique, which can lead to poor decision-making and project underperformance.
The research found a statistically significant link between a project’s perceived uniqueness and underperformance, with projects considered truly one-of-a-kind experiencing cost overruns on average 45 percentage points higher than those considered not unique. You can avoid costly mistakes by applying lessons learned and knowledge from other projects.
Faster project delivery and reduced costs
Digital tools and AI can provide experience from other projects to improve future project delivery.
AI algorithms can analyse historical data and weather patterns to indicate potential delays, allowing teams to look for opportunities to mitigate issues and improve project performance.
Improved project quality and enhanced safety
The use of AI-powered drones, along with digital twins, improve safety and quality by enabling the early detection of issues and facilitating immediate corrective actions, preventing accidents and ensuring compliance.
Risks/barriers
Our office leads identified a shortage of skilled personnel and resistance to change as the primary barriers to adoption. Local markets are experiencing skills shortages not only in traditional roles but also in emerging, technologically advanced positions. Additionally, respondents highlighted that the sector often hesitates to adopt new technology until it has been proven to be effective, efficient and achieve a level of standardisation.
Lack of skilled personnel and job displacement
The use of AI requires a skill set that is not currently widely available in the construction industry, among others.
A recent Cloudera survey of IT leaders from the US, Europe and the Asia Pacific revealed that over a third (38%) of respondents identified insufficient training or talent as a barrier to implementing AI effectively.
AI systems require specialist programming, data analytics and machine learning knowledge. Without these skills, employees may struggle to understand how to use and interpret the results produced by such systems properly.
Therefore, companies within the industry must invest in ongoing education and training to guarantee that their employees have the necessary skills and knowledge to use AI systems competently.
Furthermore, the adoption of AI can lead to changes in job responsibilities and roles, as a certain level of human oversight is essential to detect AI errors. Controls might include specific procedures for reviewing AI-generated work and training on the use of generative AI.
Resistance to change
The construction industry has traditionally been slow to adopt new technologies and is very cautious. Projects are high-risk and resource-intensive, which can stifle innovation and there is a tendency to rely on familiar methods.
The fragmented nature of the industry hinders the data sharing necessary for effective AI implementation.
Data privacy concerns
One of the chief concerns is data security. Potential scenarios include internal or client data loaded into a tool only for it to be unintentionally shared with other users or via a malicious attack.
To mitigate the risk, companies like Gleeds are developing in-house AI solutions to protect sensitive data. Employee training on secure data handling practices and creating AI in work processes are also vital safeguards.
Technology reliability issues
The Get It Right Initiative (GIRI) explains that unreliable technology can cause significant issues in the construction process, for example causing project delays due to work stoppages. Automated equipment or monitoring systems failing unexpectedly can also pose safety risks.
These issues can have knock-on impacts, such as cost overruns and undermining trust, reducing the willingness to adopt new technologies.
High implementation costs
Implementing digital tools is essential to stay competitive and optimise resources, ensuring the efficient use of materials and labour to minimise costs and wastage.
However, initial costs can deter some firms, with costs ranging from security measures to training staff; these can be a big commitment.
Regular reviews of the value and benefits will facilitate continued investment and the exploration of new solutions as they come to market.
© 2024 Gleeds - all rights reserved
Gleeds privacy policy | Cookie Policy | Modern slavery & human trafficking statement | Equal opportunities & diversity policy