Why AI integration is critical for mega-projects: Lessons from the GCC

The application of advanced technologies such as AI and ML in construction is no longer a thing of the future, but a present-day necessity that poses an array of benefits, ranging from streamlined project execution to hassle-free maintenance, post-construction.

Today, a significant per cent of businesses embrace cutting edge, AI-driven technologies to streamline construction processes, cut down expenses and enhance project outcomes.

Colossal projects such as NEOM have set exemplary precedents for the application of AI and Machine Learning (ML) in construction.

Within the broader GCC landscape, there is heavy flow of investments into technological advancement supported by the region’s tech-savvy population and various government strategic initiatives.

For instance, the ‘UAE Strategy for Artificial Intelligence’, is a harbinger of the impending global shift towards AI and ML.

The strategy aims to facilitate the application of AI across diverse sectors like transport, healthcare, renewable energy, and education, harnessing the technology’s transformative potential to enhance service delivery, boost productivity and foster sustainable economic growth rooted in innovation.

Yet, the remaining sizable per cent remain hesitant to make investments.

The integration of AI into construction practices, is not as a fad but a critical strategic imperative that can positively transform project lifecycles, from design, bidding and financing to procurement, construction operations and asset management.

There are six key reasons why businesses in the construction landscape must embrace AI as an integral facet of their operations, before it’s too late to catch up with project deadlines. 

Enhance project execution and avoid budget constraints

AI is an essential tool for businesses that struggle to keep up with projects’ budget constraints, especially in the case of mega-projects that tend to exceed their budgets. Artificial Neural Networks can help predict such budget overruns by analysing project size, contract type and the competence level of project managers.

AI predictive models can also analyse historical data on the start and end dates of previous projects, to create realistic timelines for future projects. It can also facilitate remote access and practical training material for staff, to empower them with requisite knowledge and skills. This helps cut down resource on-boarding time, consequently expediting project delivery.

Tackle cross-functional issues

Interoperability issues and clashes between architectural, engineering and MEP models and plans often hinder successful project execution.

This can be tackled by utilising AI-powered generative design, integrated into BIM technology, which can pre-emptively identify and mitigate potential conflicts by leveraging ML algorithms.

These can generate several design variations as per project constraints, minimising rework, optimising 3D models, and ensuring seamless coordination among different teams.

Risk management and mitigation

Construction projects come with several risks pertaining to quality, safety, time, and cost. The risk quotient is often higher in the case of larger projects as it involves multiple contractors.

Project managers can utilise AI and ML solutions, as well as AI integrated construction site management software to monitor on-site operations through cameras and visual recognition technologies, thereby identifying and mitigating hazards to enhance safety outcomes and project efficiency.

Automation shaping the future

Innovations such as autonomous bulldozers and robotic assembly lines not only accelerate project timeline, but also enhance workplace safety and wellbeing by replacing humans to perform hazardous and repetitive tasks. Automation will play a major role in shaping the construction industry’s future, as these advanced mechanisms help build components with precision and optimise resource allocation.

This gives team members the time and ability to focus on complex construction nuances that require creativity and expertise. For instance, Trimble’s cutting-edge solutions can be integrated with various hardware devices and third-party systems to optimise integration capabilities and enhance user experience.

Big data analytics

With the use of sensor data and drone-captured images among other sources, big data analytics can offer valuable insights into all aspects of a construction site. By analysing this data in real-time, construction software can provide actionable insights and empower project managers to make informed decisions.

In the digital era, AI systems are regularly exposed to exponential amounts of data, which is beneficial in the long run. For instance, construction sites are crucial sources of data and AI systems can learn from this data to consistently improve their capabilities.

The majority of such data is generated through mobile devices, drone videos, security sensors, and building information modelling (BIM) among others. With access to such expansive data, customers and industry professionals can gain valuable insights into various processes.

Post-construction maintenance

Building managers can leverage AI integrated inspection management software, post-construction, to collect information about different structures through sensors, drones, wireless technologies, advanced analytics and AI-powered algorithms. This can help assess the integrity and performance of buildings, bridges, roads and other elements in a built environment.

Thus, AI integrated safety inspection software can detect potential problems early on, determine when preventative maintenance is required, and direct human behaviour to ensure optimal safety.

In order to realise these benefits, it is pertinent for businesses to overcome challenges such as high initial costs, vast data management, resistance to change and skill gaps among employees.

By proactively tackling these challenges and embracing AI, companies can position themselves for enduring success in the construction landscape, setting new benchmarks of excellence in the industry.

The author, Paul Wallett, is regional director of Trimble Solutions, Middle east.

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