Cost and schedule issues are information management issues
6 July 2026
What’s driving the demand for infrastructure digital twins – and what’s holding them back?
16 July 2026
The demand for digital twins focused on maintaining the resilience of key infrastructure is surging. Ashish Kolte of DataIntelo reviews what’s driving that demand and the issues holding digital twins back.
Somewhere in a control room, a software model of a city’s water network flags a pressure drop at 3:47am. It cross-checks the anomaly against pipe age and soil data, puts the odds of failure within 72 hours at 78%, and dispatches a crew hours before a resident would ever have picked up the phone to report a burst main.
This is exactly the kind of silent, automated process that the digital twins of infrastructure resilience have been designed for, which is precisely why there is currently such explosive market growth in this part of the construction technology sector.
In our latest market research report, we valued the global market size of the infrastructure resilience digital twin at $9.4bn in 2025 and anticipate it will reach $38.7bn by 2034, growing at a CAGR of 17.1%. This comes as no surprise considering the current state of the construction industry, which has traditionally been dependent on drawings and spreadsheets.
Three forces are driving this growth.
The first is plain climate risk. Natural disasters accounted for more than $140bn in insured losses in 2024, double the inflation-adjusted amount of two decades ago. Boards, insurers and regulators no longer see a reactionary approach as a satisfactory plan. Digital twins allow asset owners to run thousands of climate simulations for a 100-year flood, a category-5 wind load, a seismic event against the real-time simulation of their physical assets. The US Army Corps of Engineers’ digital twin of the Louisiana coastal protection system, which models sea-level rise impacts on levee performance out to 2075, has become something of a reference project that other agencies across Europe and Asia are now replicating.
The second is public money with digital strings attached. The US Infrastructure Investment and Jobs Act alone allocated in excess of $65bn to grid resilience, $55bn to water infrastructure, and $110bn to roads and bridges, with digital monitoring now explicitly required as part of the grant conditions. The European Union’s Recovery and Resilience Facility and the Japanese ¥25 trillion infrastructure maintenance fund are following the same trend.
Governments aren’t just funding resilience: they’re mandating that it be demonstrable, auditable and digital, which pushes contractors and operators toward twin-based reporting whether or not they’d have chosen it on their own.
The third is the unglamorous but essential drop in the cost of instrumentation. The price of industrial IoT tech such as vibration sensors, strain gauges and acoustic leak detectors, which provide information for a digital twin, has declined by about 65% since 2018 due to advancements in micro-electromechanical systems process technology and lower-cost wireless communication protocols. That has quietly turned sensor-dense monitoring from a luxury available only to national utilities into something a mid-sized municipal water authority can now justify.
Where AI changes the calculus
Early digital twins were largely visualisation tools useful for situational awareness, but not much more. What’s changed the economics is the layer of machine learning now sitting on top. Field studies across 47 transportation and utility deployments found predictive maintenance accuracy of 87.3% for AI-augmented twins, against 61.4% for rule-based monitoring alone – a gap wide enough that finance teams, not just engineers, are now pushing for adoption.
Platform vendors have responded accordingly. Generative AI-based scenario modelling is now part of Siemens’ Xcelerator platform: it reports about $2.1bn in digital twin revenues for 2024, an increase of 19% year-on-year. Microsoft has embedded OpenAI models into its Azure digital twins service for government and utilities market segments already under enterprise licensing agreements with Microsoft. IBM’s Maximo Application Suite continues to lean on its asset-management depth for regulated utility buyers.
None of this is incremental tinkering – it’s a repositioning of digital twins from passive dashboards to active decision-support systems with a measurable line to the balance sheet.
Software still leads, but services are catching up
On a per-component basis, software continues to take the lion’s share of the market, accounting for 54.2% of the total 2025 revenues, or around $5.1bn, owing to the recurring revenue model of SaaS, along with the steep costs involved when it comes to switching to a new platform. However, services, which account for 29.6% of the total revenues, are witnessing a steady growth rate of 16.4% CAGR, due to the sheer amount of integration required to set up an end-to-end solution, including model calibration, systems integration and change management processes that take between 12 and 36 months on average.
By application, asset management holds the largest share at 31.4%, driven by the sheer scale of ageing infrastructure that needs to move from calendar-based to condition-based maintenance – a shift that has documented cost reductions of 15%-28% where it’s been fully implemented. Disaster management is the fastest-growing application, expanding at 19.8% CAGR, as cities including Singapore, Rotterdam and Los Angeles build twins capable of simulating evacuation routing and infrastructure damage cascades in real-time during a crisis.
Regionally, North America still leads with a 36.8% share, but Asia-Pacific is the fastest-growing region at 18.9% CAGR, propelled by China’s infrastructure investment drive, India’s Smart Cities Mission spanning 100 cities and a $14bn pipeline, and Japan’s Society 5.0 framework.
The ROI is becoming harder to ignore
Given that the industry has always had trouble adopting innovative technology, the results that have been recorded through early full-scale implementations are quite impressive. Managers using AI-augmented resilience twins show return on investment at between 2.8 to 6.4 times over five years, while maintenance savings amount to between 18% and 28%, unplanned downtime reduced to a maximum of 32%, and time to detection for infrastructure anomalies reduced from an average of 4.2 days to below six hours.
That said, the path isn’t frictionless. Roughly 34% of digital twin pilots in the infrastructure sector fail to scale beyond proof of concept, and the barriers are more organisational than technical: 41% of operators cite internal resistance to changing established processes, and 38% report struggling to hire or retain staff with the combined domain expertise and data science skills the work requires.
Data interoperability between legacy systems and modern platforms, along with the cybersecurity exposure that comes from connecting critical infrastructure to networked simulation environments, round out the list of genuine constraints on how fast this market can actually move.
What comes next
However, perhaps one of the biggest changes coming our way does not involve any innovation in sensors or algorithms. Rather, it is a workflow change that is already being experienced within the construction industry itself. With 19650-compliant handovers on the rise, more contractors are being tasked with providing comprehensive digital asset information at project delivery rather than providing a pile of documents in pdf form.
It is believed that such a shift would reduce the average timeframe for digital twin infrastructure implementations by roughly 50% by 2028, effectively incorporating resilient intelligence right from the get-go. In an industry that is forced to operate under pressure to construct better and faster, spend more intelligently, and withstand a climate that is becoming less and less predictable by the day, that is the true potential of this technology.
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