In 2020, Spacemaker, a Norwegian start-up applying machine learning to architecture, was acquired by Autodesk for US$240 million. Despite exciting developments in AI and machine learning, few companies were focusing on AI applications for construction and real estate. Spacemaker was an exception.

According to McKinsey, construction was by far the weakest sector as measured by productivity growth since 1995. “If you look at the efficiency curve in [the construction] industry, it is sinking,” said Janne Aas-Jakobsen, founder and CEO of Consigli, a software-as-a-service (SaaS) provider for real estate developers and contractors. She added that 85 percent of projects face cost overruns, with almost 50 percent experiencing cost overruns of more than 15 percent. The sector is primed for disruption.

In a webinar with Aas-Jakobsen, we explored this untapped opportunity at the intersection of technology, construction and finance, and how her company applies AI to the early-stage design of new building projects to massively reduce costs and carbon emissions.

Ripe for reinvention

When planning to construct a new building, developers need to solicit bids from contractors, obtain building permits and get investors’ buy-in. Early-stage calculations and plans are prerequisites to develop specifications on which contractors could develop binding bids. At the same time, developers contract engineering consulting firms to provide detailed specifications of technical systems – from electrical to ventilation, heating, cooling, water and fire prevention. An estimated 10 percent of total new real estate development costs are tied to early-stage engineering – a figure that’s fairly consistent across geographies. 

It’s a highly complex task with many disciplines involved, and regulatory requirements add more complexity to the mix. For instance, counties and municipalities in the United States had reportedly over 93,000 different building codes, which means companies building prefabricated houses must adapt to the specific codes of each jurisdiction. 

“We have been doing things the same way for years, regardless of whether we are using pen and paper or computer-aided design programs,” said Aas-Jakobsen. As information is sequentially passed on from one party to the next, it’s inevitable that quality and complexity in the final design are lost. Fortunately, everything within that complexity is known: the laws of physics, the building standards, what global suppliers can provide and so on. The design process in construction engineering was ripe for reinvention. “Finding an optimal solution to a complex puzzle of knowns is what AI is good at,” she surmised. 

As Aas-Jakobsen searched for methods to solve these problems, she took inspiration from ship construction, where algorithms were used to size and design engine rooms. In 2020, she founded Consigli, which uses AI to facilitate early-stage mechanical and electric design – from lighting and sprinklers to ventilation. 

Engineering a solution

The SaaS product, the “autonomous engineer”, enables real estate developers and construction contractors to reduce their expenses while maximising usable space. It’s capable of reorganising rooms and parking areas for space optimisation, which is more complex than what appears on paper: cars need to be able to move out of parking lots, guests need to be able to escape from their hotel rooms in an emergency, and plant rooms need to be large enough to operate and maintain – but no bigger than necessary due to the high costs.

In addition, the AI co-worker provides a wide range of services, including generating reports customers expect from construction engineers and ensuring consistency and compliance. It flags inconsistencies between the building model and tender materials, misalignment between tenants’ needs and the spatial design, and non-compliance of designs and specifications with building codes. 

Real estate developers can log in to the web-based software, create a project and upload the building information model (BIM) from the architect, along with relevant information such as tenant specifications, room mix or technical details such as energy requirements. The autonomous engineer would then update the BIM to include optimal room layouts and systems such as electrical, cooling and fire prevention.  

This flow of communication isn’t too different from how one might work with consultants, but speed is of the essence. Whereas engaging with consultants can take months, the autonomous engineer can produce actionable output in one to two days, saving 15 to 20 percent in costs. 

A vision for more sustainable construction 

The beauty in the tool isn’t only in lowering the risks and costs of real estate development, but also its carbon footprint – by reducing the use of concrete, ducts, pipes and cables, alongside potentially decreased cooling needs.  

“We do the boring stuff, the boring part of sustainability. It’s about using less,” said Aas-Jakobsen. But in the context of the construction sector, which is responsible for 40 percent of annual global emissions, the impact of using less materials is anything but mundane or negligible. Consigli’s vision is to reduce construction materials by 20 percent and, in doing so, decrease embodied carbon in the industry. 

Resistance to change is inherent among real estate companies. After all, it takes time to change workflows. Moreover, risk and liability are common concerns, since real estate development projects involve developers, engineering consultants and contractors who are liable for various aspects of the project. This is where a tool to help developers focus on optimising the early stages of the design process can reduce risks considerably.

In one instance, Consigli helped a client identify discrepancies in the insulation capacity of materials (U-value) and the conditions of green financing. Had the variance not been flagged at the design stage, the building would have been built outside the scope of the financing conditions, which could result in major reworking and waste. Financial gains may be more apparent in some cases, such as the example of Norwegian real estate company Entra. It had bought a hotel and sought Consigli’s services to find ways to increase the property’s value. The solution offered was to design spaces to incorporate more hotel rooms, which didn’t only result in increased operating revenue, but a huge premium when the property was later sold.

As improved planning lowers risks and costs while increasing efficiency, sustainability follows naturally. With a clear business case for sustainability, little convincing is needed. Indeed, Consigli caught the attention of global infrastructure engineering giant AECOM, which acquired the start-up in November 2025 for an estimated US$390 million. Ultimately, its ability to boost construction efficiency and margins, while generating solid sustainability benefits is not only a clear strategic differentiator for AECOM, but is also in line with its sustainable legacy strategy, helping it  to leave “a positive, lasting impact for communities and our planet".