AI applications need solid data foundations to drive real benefits.

Two words have been dominating technology conversations across all industries in recent times: artificial intelligence (AI). Construction is well placed to seize the opportunity for significant digital transformation through the application of AI technologies in the Middle East – including generative AI (GenAI), which has gained prominence since the release of ChatGPT in November 2022.

It may be difficult to imagine what benefits AI will bring to day-to-day operations in a sector where so much of the work is manual and undertaken by people on site. The answer lies in enhancements to functions like quality control, trend forecasting and risk analysis playing a key role in the future of Middle Eastern construction. And AI is expected to apply to more operational areas.

As Deloitte’s 2024 Engineering and Construction Industry Outlook report states: “With the rise of generative AI and other disruptive technologies, the sector is now seemingly poised to realise improvements in project design, schedule optimisation, cost controls, site inspection, safety, compliance and quality assurance.”

But how?

A solid foundation of data

Construction professionals understand the importance of firm foundations. The same applies to creating and using AI applications, which need solid data foundations to drive real benefits. Without sufficient data inputs, it’s difficult to create anything useful or meaningful from AI outputs. There’s no shortage of data in construction, but that data is often siloed in different systems, making it difficult to consolidate. Integrated technology platforms are an important part of the puzzle, but equally important is helping teams to learn how to get the most out of any software investment you make. Implementing easy-to-use, intuitive AI software can help to maximise the tools at your workforce’s disposal. 

It is important to upskill on-site workers to collect the data that’s needed to power them from all parts of the project.

It is important to upskill on-site workers to collect the data that’s needed to power them from all parts of the project.

A recent McKinsey report revealed that “many companies in the Middle East and North African construction industries either cannot yet collect the data required to train AI models or do not have the necessary capabilities to stitch what they have together.” This is the first area for construction companies to tackle.

Any outputs are reliant on the material the AI tool is trained on – the quality and scale of the resources it can draw on to generate responses – and the prompts or algorithms applied to generate them. Companies need high-quality, consolidated data to make the best use of AI and a clear plan to continually develop the workforce’s AI skills to ensure optimal use of technology.

Sources of relevant data can range from Internet of Things (IoT) sensors, CCTV systems, financial reports and more. Once an organisation has confidence in the data they are collecting, they can begin to integrate AI capabilities into their operations to improve predictability and efficiency.

This capability can unlock faster, better decisions in back-end functions like finance, as well as help make better decisions on site using more holistic, up-to-date information for the most accurate context. In fact, Operations is often a good place to start road testing AI as the department will already have established measurement cultures in terms of efficiency and cost. Begin by experimenting with new ways of working in one area. Making adjustments and improvements to optimise existing practices and processes can be a much better way to start than aiming for a ‘big bang’, organisational-wide transformation. 

It’s important to note that the key to the successful application of AI lies with people as much as it does with the technology. Upskilling the workforce in all parts of the business – in office, on site and with external parties such as subcontractors and all parts of the supply chain – is vital for real progress. This includes educating knowledge workers to use AI tools and training on-site workers and subcontractors to collect the data that’s needed to power them from all parts of the project.


Use cases for AI on construction sites

Machine learning, GenAI, data analysis, image recognition and predictive analytics (all subsets of AI) are some of the applications that the construction industry can benefit from, both on and off site. The overarching aim is to support more efficient operations and create a safer environment for workers.

Here are four ways that AI can help:

1. Real-time monitoring of job sites:  Using advanced image recognition, AI can help monitor job sites through CCTV systems and apply machine learning algorithms to identify potential risks and hazards in areas under surveillance. Once a camera detects a risk or anomaly, the system sends automated alerts to the relevant supervisor, allowing them to check the area of work in question and reduce the risk of accidents.

2. Targeted training and education: The same data can be used to identify areas where employees may benefit from supplemental education or training. For example, if a camera detects that personal protective equipment is not being used as intended or equipment is being operated in an unsafe manner, tailored training can be undertaken to reduce risks going forward.

3. Conversational AI on site: AI chatbots are beginning to make their presence felt on construction sites. Navatech’s AI Conversational Assistant is an application that allows workers to access safety information in different languages, with a user-friendly interface that resembles the messaging tools that employees are already familiar with. The data collected via workers’ enquiries helps companies understand where additional information or education may be needed.

4. Predictive analytics for maintenance and safety: Using historical data from IoT sensors, AI can predict events such as wear to machines or malfunction, helping construction teams to target maintenance efforts more effectively. AI can also be used to analyse historical data to identify trends and patterns that reveal common factors causing accidents or outages, allowing teams to mitigate these risks in the future.

In PwC’s article Reshaping the Middle East: A CEO’s playbook to win the $23.5 billion Generative AI opportunity, Tony Karam and Jad Baroudi urge construction leaders to adopt AI: “Executives in the Middle East should seize the opportunity without delay. Companies that merely watch from the sidelines risk falling behind, while their forward-thinking counterparts that adopt GenAI stand on the verge of gaining a significant competitive edge.”

It’s clear that artificial intelligence offers a world of potential and opportunity for improving construction operations and safety performance. By refining data and helping your workforce gain the relevant technical skills, you can ensure your business has built the foundations it needs to benefit from AI today, and the associated benefits to come.