How can AI enhance construction project management and what are its limitations?

  • Insights
  • How can AI enhance construction project management and what are its limitations?
About this article
Alyaa Al Wahab


Alyaa Al Wahab


Digital Transformation , Future Thinking
Market Insights

Sign Up for Market Trends & Insights


According to Harvard Business Review, approximately US$48 trillion is invested annually in projects.

However, only 35% of these projects are deemed “successful,” primarily due to the limited maturity of project management technologies. If cutting-edge advancements like Artificial Intelligence (AI) and other technological innovations could enhance the success rate of projects by a mere 25%, the resulting value would equate to trillions of dollars.

AI – the ability of a digital computer or robot to perform tasks commonly associated with intelligent beings – has seen rapid growth and evolution in recent years, revolutionising multiple industries. The construction industry is no exception. The field of construction project management – a multifaceted discipline that involves directing and organising each part of the construction project life cycle to deliver projects on time and on budget – can certainly benefit from the implementation of AI technology. However, like any other technology, AI does have its limitations. Here we explore the benefits and shortcomings of AI in enhancing construction project management.

The advantages

One of the most obvious benefits of AI for construction project management is the automation of repetitive tasks, such as data entry, form filling and report generation. By automating these recurrent and time-consuming duties, project managers can then focus their efforts on more pressing or creative tasks, allowing them to make greater impact on projects.

Assisting with repetitive responsibilities, however, is not AI’s only benefit in construction project management. Other advantages include:

  • Virtual and augmented reality: Enhancing project visualisation by creating 3D models and simulations that can be used for design reviews, safety training and communication with stakeholders is an extremely useful offering by AI. This helps project managers to improve project understanding and reduce errors.
  • Predictive analytics and risk management: AI can also be used to analyse data from various sources such as sensors, weather forecasts, as well as past historical data and project databases to predict potential risks and identify areas for improvement. The results of which can help project managers make informed decisions and take proactive measures to mitigate risks.
  • Quality control: AI technology can also assist with monitoring construction sites and identifying potential safety hazards, quality issues and deviations from the design. Project managers are therefore empowered to take corrective action in real-time, thus improving the quality and efficiency of the project.
  • Resource optimisation: Analysing data from various sources such as project schedules and labour productivity to adjust resource allocation is yet another benefit offered by AI, allowing project managers to reduce waste, improve productivity, and complete projects within budget.

The limitations

Despite AI’s ability to help project managers make better decisions, reduce risk, improve quality, and increase efficiency, AI also comes, unsurprisingly, with limitations:

  • A lack of context and understanding: AI systems may not be able to fully understand the nuances of a project or its site, the impact of external factors or the unique needs and expectations of specific stakeholders.
  • Data quality issues: AI relies on accurate and comprehensive data to make informed decisions. Construction projects generate a vast amount of data, but much of it can be unstructured and difficult to analyse. This can limit the accuracy of AI algorithms and make it difficult to provide actionable insights. If the data used to train the AI is incomplete, inaccurate, or biased, the system’s output could also be unreliable, meaning decisions are being made without a full, accurate set of information.
  • Implementation cost challenges: Implementing AI in project management can be complex, time-consuming, and costly. It may require significant investment in technology and expertise, not to mention potentially large changes to existing processes and systems – something which, in some companies, could be met with scepticism or resistance.
  • Dependence on technology: Finally, AI can create a dependency on technology, which could prove problematic if the technology fails or malfunctions. Construction project managers would therefore need contingency plans in place to address these issues if and when they arise.

It is also important to acknowledge that AI algorithms are inherently limited in their ability to handle unexpected situations that arise rapidly, primarily because they are trained on historical data. This lack of agility in unanticipated circumstances is a fundamental characteristic of AI systems. Unforeseen and highly improbable events that carry significant consequences are sometimes referred to as Black Swan events, a concept popularised by essayist and mathematical statistician, Nassim Nicholas Taleb. The COVID-19 pandemic serves as a prime example of such an event, wherein AI systems would have faced significant challenges in swiftly formulating effective solutions due to their reliance on past data.

When it comes to construction project management and Black Swan incidents, such as a physical construction failure, the indispensable role of human leadership and oversight becomes evident with AI unable to adequately replace the critical skills required to anticipate, mitigate and navigate such an event.

There is no doubt that AI can create huge value in construction project management by increasing efficiency, improving project quality and reducing costs. However, it is important to ensure that AI systems are properly integrated into project management processes and these systems are used ethically and responsibly.

Human-centred skills – such as leadership, conflict resolution, consensus building, motivation and persuasion, decision making, emotional intelligence and creative problem solving – are all essential to keep any project running smoothly. These skills are currently outside the realm of AI. Therefore, AI is at its best when it is a ‘co-pilot’ that enhances, rather than replaces, professional personnel.

AI systems can assist and complement inimitable, human-led skills and processes, maximising efficiency and project results. In construction, that ultimately means better places for people.