Cranes, Code and Co-Pilots: Why AI is Finally Cracking Construction and Property
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Read our deep dive on built-world AI below. You can read our other article on what sets ANZ and Southeast Asia AI companies apart, “The Moats That Matter in AI,” here. March 2026
A typical construction project generates thousands of documents: contracts, drawings, requests for information, change orders, daily site logs, safety reports, photos taken on phones and scribbled punch lists that may or may not survive the rain. Industry estimates suggest that up to 80 per cent of this data is unstructured, scattered across PDFs, spreadsheets and email threads that rarely talk to each other. Germany’s RIB Software found that 96 per cent of construction data goes unused, and that one in eight working hours is spent simply looking for project information.
For decades, the industry’s answer to this was more paper, then more tablets, then more cloud folders. Each wave of digitisation moved the filing cabinet from the site office to the server but did not change what was inside it. The information remained messy, fragmented and largely illegible to machines.
Property is no less trapped. Real estate marketing is one of the world’s most language-intensive, localised and relationship-driven industries, yet its daily workflows have barely changed over decades: lead generation, tour scheduling, compliance management and chasing signatures still consume the bulk of an agent’s working day. The data exists, but it sits in listing portals, valuation models and lease agreements that no machine could previously read with any useful accuracy.
What has changed, and what makes the current moment different from every previous attempt to modernise the built world, is that AI can now read the mess. Large language models can interpret a 200-page contract. Computer vision can flag a scaffold defect in real time. Generative AI can convert a planning brief into a code-compliant building design in seconds. These are not incremental improvements. They represent a new capability: machines that can finally process the unstructured, multilingual, photo-heavy data that these industries have always generated but rarely been able to use effectively.
Late last year, Bessemer Venture Partners published a roadmap for AI in the built world, arguing that construction and real estate represent the next major software frontier, driven by multimodal LLM-powered workflows and new forms of human-machine collaboration. These industries, roughly a quarter of American GDP yet less than 3 per cent of the spend allocated to technology, are now meeting an AI stack capable of automating workflows that have historically required expensive human labour. Bessemer identified nine categories of opportunity, from design generation through to property co-pilots and construction robotics.
Capital allocation is catching up. Global ConTech venture funding hit US$3.7 billion through the first three quarters of 2025, up 27 per cent year on year. PropTech venture investment reached US$16.7 billion for the full year. ServiceTitan’s initial public offering gave the trades category its first public benchmark at around US$9 billion during its first day of trading in December 2024 (although its stock fell by nearly 40 per cent during the broader software sell-off).
What has not been widely appreciated is how much of this wave is already building across Australia, New Zealand and Singapore: massive industries, very low technology penetration, strong regulatory drivers, chronic labour shortages and a growing cluster of AI-native companies that global acquirers are willing to pay full price to own.
The industries beneath the software
The scale beneath is worth pausing on. Australia’s construction sector generated A$634 billion of total income in 2023-24, 7 per cent of national GDP (tradies contributing A$276 billion). The residential property stock alone is worth A$12.4 trillion, roughly three and a half times every security listed on the ASX. New Zealand adds NZ$32.5 billion in construction gross value added (7.8 per cent of GDP). Singapore awarded US$44.2 billion in construction contracts in 2024. Yet Deloitte and Autodesk’s 2025 survey of roughly 900 construction firms across six Asia-Pacific markets found that each additional technology adopted correlates with a 1.14 per cent revenue increase, and that firms with higher digital maturity report 50 per cent fewer safety incidents.
What AI is actually doing on site
The deepest cluster of AI activity in the region sits in on-site coordination and safety. Australia’s workplace health and safety regulation is among the most stringent in the developed world, its housing pipeline remains above 200,000 dwellings under construction, and its labour shortage is acute. All three factors create demand for software that automates the administrative burden site supervisors carry every day.
Sitemate, which closed a A$27.5 million Series A in late 2024 led by Blackbird Ventures, replaces paper-based site records with structured, queryable data. CEO Hartley Pike describes the approach as “designing built-world specific tooling and then plugging into the general business stack.” The significance is not the digitisation itself but what it enables: once field data is structured, it becomes the training set for AI that can detect patterns, flag anomalies and predict failures.
SafetyCulture, valued at about A$2.5 billion, is the category’s incumbent, with its management platform dominant across Australian construction and an AI roadmap spanning anomaly detection and automated corrective actions. In Singapore, Ailytics uses computer vision to monitor sites for safety compliance, and was named the country’s 11th fastest-growing company in January 2026. HammerTech, backed by US$70 million from Riverwood Capital, is layering AI analytics over its safety platform across more than 20,000 projects globally. Visibuild, backed by Skip Capital, is building AI to auto-classify defects from site photographs. The pattern is consistent: digitise the workflow first, then layer AI on top. The second act changes the economics.
Estimation in hours, not weeks
A parallel shift is happening in pre-construction. Buildxact, an Australian residential estimating platform, launched its Blu AI assistant in 2025. CEO Stephen Yates says AI now delivers up to A$450,000 worth of estimating capability “with little or no increase in your marginal cost.” That is the kind of statement that would have been implausible five years ago. It is now a product feature.
ProcurePro, which powers over 3,000 projects worth more than A$70 billion, has committed to shipping an AI procurement assistant that flags risk autonomously. Founder Alastair Blenkin’s pledge to “save another million construction admin hours” in 2026 captures a category where the debate is no longer whether AI works in construction but how fast it ships.
Property co-pilots and generative design
PropHero, which in February 2025 raised a A$25.1 million Series A backed by Bailador, Fifth Wall and Samaipata, runs machine learning across more than 200 million data points to identify high-yield investment properties. At the time of the raise, the company reported roughly A$35 million in run-rate revenue, 200 per cent annual growth and profitability. Ohmyhome’s HomerAI engine won a Singapore Business Review Technology Award, having achieved 73 per cent of homes sold above market value, and 65 per cent secured offers within a week.
Archistar, founded by Dr Ben Coorey, can generate hundreds of code-compliant 3D building designs for any site in seconds. In February 2026, Dr Coorey was recognised at the Australia Day Awards Gala in Washington, DC, for deploying the platform to accelerate rebuilding after the Los Angeles wildfires. Neara, which develops physics-based digital twins for critical infrastructure, closed a A$90 million Series D in February 2026, valuing the company at more than A$1.1 billion and placing it among Australia’s tech unicorns. It is not alone in attracting serious capital.
The capital is following the code
Deal activity reinforces what product roadmaps already signal. We mapped more than 20 construction, trades and property software transactions across ANZ and Singapore over the past two years, spanning growth equity, PE-backed roll-ups, strategic mergers and acquisitions and founder-led venture rounds. Clear themes have emerged: global acquirers entering ANZ and Singapore, platform consolidation across trades and a consistent AI angle. Globally, AI-referenced SaaS acquisitions accounted for over 70 per cent of all SaaS M&A transactions in 2025. AI capability is no longer a premium for acquirers; it is a baseline expectation. These patterns extend into Europe, where our associated firm GP Bullhound has advised on build-world technology including US-based Spectra Precision’s acquisition of Unicontrol (a consolidation play in machine guidance and site autonomy), and PSG Equity’s investment in One Click LCA, which specialises in decarbonising the construction and manufacturing industries.
CoStar Group’s A$3 billion acquisition of Domain Holdings was the biggest PropTech deal in ANZ history. Global consolidator JDM Technology Group acquired Brisbane-based Buildlogic, further strengthening its regional construction-software footprint. MRI Software entered the region twice, acquiring Proptech Labs and Anacle Systems to drive AI automation. EQT took a majority stake in Australia’s PropertyMe and acquired Singapore-based PropertyGuru. Simpro, under K1, has been executing a multi-acquisition roll-up including BigChange and AI-focused Delight; its CEO Fred Voccola says the company is building “the world’s first and only AI-first operating platform for the trades.” Not to mention UK-based The Access Group, which in recent times has gobbled up ANZ tradie SaaS platforms Tradify and GeoOp.
What has not yet been built
Several areas of opportunity in built-world AI remain lightly addressed. Construction knowledge management has partial coverage through players such as Sitemate and Mastt (which raised A$9.5 million in a Series A led by OIF Ventures), but opportunities in natural-language project AI remain mostly open. Property management AI, the category scaling fastest in the US, has no direct ANZ equivalent, though EQT’s PropertyMe and its acquisition of an AI-enabled real-estate CRM Phoenix Software suggest pieces are assembling.
Australia has also drawn on its position as a global leader in mining robotics to push into construction, the least developed segment of built-world AI in the region but no longer a blank space. FBR’s Hadrian X, a bricklaying robot capable of completing a house shell in a day, has been in commercial operation for a couple of years. At the International Astronautical Congress in Sydney last September, Crest Robotics and Earthbuilt Technology unveiled Charlotte, a spider-like, semi-autonomous robot designed to 3D print a home by moving and straddling walls onsite. The next frontier is likely to be defined by human-machine collaboration, with operators managing multiple robots through natural language and robots working alongside crews on complex site tasks.
For founders and investors, these gaps are not weaknesses. They are starting positions.
Build enduring moats
The broader market is heading in one direction. Global construction technology is forecast to grow at roughly 17.5 per cent annually through to 2034. Australia needs 1.2 million new homes by 2029. Singapore is deep into a government-mandated construction digitalisation programme.
The companies building AI for construction and property share a characteristic that matters as AI agents compress generic software layers: the best of them own something an agent cannot easily bypass. A compliance record that regulators require. Deep vertical workflow integration. AI deployed in physical systems. A project data spine that every subcontractor writes to. True systems of record, not mere dashboards. Those are moats that compound rather than erode.
For enquiries, please contact:
Gerry Gimenez, Director of B2B Software & AI at North Ridge Partners, gg@northridgepartners.com
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