The UK Is Perfectly Positioned to Use AI and Overcome Infrastructure Project Challenges - image by pixabayThe political debate around UK infrastructure is heating up. The Labour Party in opposition recently pledged to invest GBP 1.8 billion in UK ports. It accused the current administration of years of underinvestment. Water and wastewater management is also under scrutiny. The UK’s largest water company is doing its best to shore up investor confidence after a torrid few months and debates over whether it needs government intervention.

No country is without its challenges when it comes to managing large infrastructure projects. Recent headlines should not give the impression that it is doom and gloom in the UK. The reality is quite the opposite.

The UK is uniquely positioned to allow infrastructure engineers, construction contractors, and owner-operators to address these challenges and improve project delivery and asset performance.

How? Through improved use of artificial intelligence (AI) across the entire lifecycle of infrastructure assets. Indeed, the International Monetary Fund expects the UK to benefit from the growth of AI as a result of its “robust digital infrastructure, skilled labour force, innovation ecosystem, and regulatory framework.”

Using AI for Good

Over the last year, there has been a lot of discussion about using AI-powered applications and solutions to improve project efficiency, organisational effectiveness, and infrastructure outcomes. Leveraging AI, machine learning, and other intelligent applications presents immense potential for addressing issues across the infrastructure lifecycle. Unfortunately, data is the foundation for AI-powered anything. The infrastructure sector has a large data management hurdle it must clear before the promise of AI can be realised.

Unlocking Data Is Critical for More Informed Decisions

For decades, the infrastructure project lifecycle was linear. Planning, design, procurement, construction, and operations had distinct phases with individual stakeholders, requirements, and discrete hand-offs. Each phase typically used different technologies and processes. This approach created information silos and data loss, resulting in design rework, errors, project delays, and increased costs and risks.

As infrastructure projects and their respective phases have become more interconnected, there is a real need to bring engineering, information, and operational technology systems and data together. But the reality is that an abundance of valuable data from these systems is trapped in files, models, drawings, and even paper. Unlocking this data is critical to better decision-making across the infrastructure project lifecycle, as well as for using AI-powered solutions.

Instead of generating critical project and asset data in disparate systems, infrastructure engineers, construction contractors, and owner-operators should start producing data layers with open platforms that generate digital twins.

Infrastructure Digital Twins Unlock Data and Process Silos

Digital twins have become a hot topic across every sector. What was once considered futuristic eye candy has evolved into a powerful and valuable way to combine and leverage data. Now, we can combine data from disparate sources and multiple disciplines into a holistic, dynamic representation of infrastructure projects and assets. In addition to providing a structured way to bring siloed data together, digital twins can unlock data from existing design files, essentially lighting up dark data.

When digital twin capabilities persist across the infrastructure project lifecycle, they create workflows that enable engineers to seamlessly conduct design reviews, structural analysis, and calculate carbon footprints. Digital twin workflows can help construction companies improve the accuracy of quantity take-offs, project scheduling, and more. In addition to bringing data together, infrastructure digital twins can connect processes between the different lifecycle stages of a project and asset.

As data layers are combined and processes are connected, their collective value is compounded exponentially. It is this value that provides the foundation for quickly and easily applying AI techniques and technologies to drive actionable insights and infrastructure better outcomes.

The Data Layers of Today Will Drive the AI of Tomorrow

Certain AI techniques and technologies are not new to the infrastructure sector. For example, owner-operators have already started using computer vision AI techniques to quickly identify, analyse, and detect spalling, corrosion, and other defects that can compromise the integrity of bridges, dams, rail networks, and other assets. However, what is new and what presents significant value to infrastructure organisations across the project lifecycle is generative AI.

In a sector challenged by resource constraints, delays, cost overruns, and evolving sustainability requirements, AI will prove a game-changer. Engineering and construction applications with generative AI capabilities have the potential to automate tasks, streamline workflows, improve project delivery, and ensure asset performance.

Consider this: generative AI technologies could give engineers the ability to collaborate with AI agents to generate and optimise infrastructure design. They could compare new designs to previous ones and learn from an engineer’s choices.

Generative AI could help engineers and construction managers use more sustainable building materials to reduce an asset’s carbon footprint or calculate an infrastructure project’s embodied carbon from start to finish.

Generative AI will give infrastructure engineers, construction contractors, and owner-operators the ability to experiment with real-life developments in a simulated environment, enabling more predictive activities and outcomes that will mitigate future challenges and risks. And that potential is too valuable to ignore.

Final Thoughts

Can AI address infrastructure project challenges in the UK? Yes.

However, there’s still foundational work that needs to be done. The simplest and fastest way for infrastructure organisations to get started with AI is by focusing on how data is organised, managed, used, and unused. Organisations that master data management and leverage digital twins will be best positioned to unlock the potential of AI—and whatever new technologies lay ahead.

Bentley Advancing InfrastructureBentley Systems (Nasdaq: BSY) is the infrastructure engineering software company. We provide innovative software to advance the world’s infrastructure – sustaining both the global economy and environment. Our industry-leading software solutions are used by professionals, and organizations of every size, for the design, construction, and operations of roads and bridges, rail and transit, water and wastewater, public works and utilities, buildings and campuses, mining, and industrial facilities. Our offerings, powered by the iTwin Platform for infrastructure digital twins, include MicroStation and Bentley Open applications for modeling and simulation, Seequent’s software for geoprofessionals, and Bentley Infrastructure Cloud encompassing ProjectWise for project delivery, SYNCHRO for construction management, and AssetWise for asset operations. Bentley Systems’ 5,200 colleagues generate annual revenues of more than $1 billion in 194 countries.


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