A new gold rush is looming, but instead of prospectors wielding picks and shovels, today’s pioneers are assembling sensors, servers and spatial intelligence.
Harry Atkinson is co-founder & chief customer officer at Sensat
Spatial artificial intelligence (AI) is the next frontier, enabling machines to navigate 3D environments. By integrating computer vision, LiDAR, geospatial datasets and 3D mapping, this technology allows digital systems to interpret the physical world almost as a human would.
Infrastructure that was once static, inspected on schedules and maintained using fixed assumptions, is becoming dynamic and continuously monitored. It is an evolution fuelled by rich data foundations.
The data explosion is driving engineering transformation
Across every industry, the scale of data creation, storage and processing is reshaping how assets are planned, delivered and maintained. Engineering organisations that fully digitalise their assets, and connect data across design, construction and operation, will gain a decisive advantage. Indeed, every company in the sector is under pressure to move from fragmented data centres to connected, intelligent infrastructures.
The benefits are manifold. From increased efficiency, with automation reducing costly manual surveys, to improved sustainability as smart maintenance lowers carbon footprint and material waste, and greater resilience, with predictive analytics mitigating risk from climate and ageing. Enhanced transparency, enabled by data-backed reporting, also promotes client trust.
Data is no longer a by-product; it is a powerful asset, informing decision-making, driving automation, underpinning resilience and enabling innovation.
The UK’s booming data centre market is both a symbol and a catalyst of this shift. Forecast to grow by 36% in revenue and 29% in power demand by the end of 2025, the surge reflects rising demand from AI workloads, cloud computing and streaming services. Indeed, September saw several major US tech firms pledge to invest tens of billions of pounds in the UK’s AI sector, with Microsoft, announcing a $30bn (£22bn) spending package, and Nvidia partnering with British infrastructure company, Nscale to build more data centres.
Enter spatial AI, the next leap forward
Connected data foundations underpin spatial AI, the next major evolution of the technology, helping machines to understand the physical world in context. Spatial AI allows systems to map, recognise and interpret their environment in 3D, combining sensor data, satellite imagery, historical performance records and environmental signals.
Traditionally, infrastructure was built, operated and repaired based on design assumptions and periodic inspections. Once completed, the data used to create it became static. AI changes that fundamental relationship. The technology is turning site monitoring and asset management into a live process that allows engineers to continuously monitor asset health.
Spatial AI uses IoT (The Internet of Things) sensors to collect and stream real-time data from specific pieces of infrastructure. Algorithms then analyse this data to activate predictive maintenance. This allows resources to be optimised, reducing the need for costly emergency interventions, as well as extending the longevity of an asset.
In short, infrastructure becomes a living system: self-reporting, amassing intelligence and communicating risk. For public-safety-critical assets, this advance is pivotal.
Building rich data foundations
At the centre of the spatial AI evolution are digital twins: dynamic, data-rich digital replicas of physical assets, networks or even entire cities. Fuelled by AI, they allow engineers to simulate “what if?” scenarios, model extreme weather events and test potential interventions, without any disruption to physical infrastructure.
Digital twins enable engineering firms to create a single intelligent ecosystem by integrating information from the design, construction and operation phases – using sources like GIS, building information modelling (BIM) and IoT sensors – into a single representation. Spatial AI models then interrogate this data to identify complex relationships and patterns within a real-world environment.
The benefits are tangible, from improved decision-making based on being able to visualise asset performance over time, to faster project delivery thanks to the ability to design and iterate virtually. Lifetime costs are also reduced because maintenance is based on real-time condition, not arbitrary cycles, while safety is heightened because vulnerabilities can be predicted before they fail.
Creating the digital backbone
Organisations that digitise their assets and invest in building robust data will be the ones to thrive and survive. Moreover, those who adapt early will shape how the infrastructure evolves over the next century.
In previous gold rushes, many prospectors went home empty-handed and fortunes were made by those selling picks and shovels; the essential tools that enabled others to succeed. Engineering firms that build the digital backbone, equivalent to the picks and shovels, will be poised to prosper.
- Harry Atkinson is co-founder & chief customer officer at Sensat
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