Francesco Iorio is CEO of Augmenta, the company automating building design for the construction industry using generative AI.
Dubai’s Museum of the Future is both a window into the world that new AI tools will enable for the construction industry and the embodiment of it.
The museum’s structure is one of the most sophisticated applications of AI in construction. Its designers developed specialized algorithms to optimize it, saving energy by 25% while achieving a LEED Platinum certification—indicating the building was designed for the highest level of energy efficiency and built as sustainably as possible.
While the project is a singular achievement, the tools used to design it are now available for project developers, architects and engineering design professionals of all stripes.
This democratization of automation and generative design capabilities promises that the industry can develop and build any building with sustainability in mind. Moreover, the industry can achieve all of this without the additional costs or extended timelines that currently deter it from foregrounding sustainable principles.
The Regulatory Environment Driving Change
High costs may make developers reluctant to embrace sustainability, but a global regulatory environment increasingly demands it. Embodied carbon accounts for roughly 11% of the warming emissions heating the planet, raising the specter of more frequent and intense climate events such as hurricanes, floods and fires that damage infrastructure and increase construction demand.
This regulatory landscape is rapidly evolving. The EU’s Energy Performance of Buildings Directive mandates zero-emission new buildings by 2030, with public buildings complying by 2028, and its Emissions Trading System will tie building energy costs directly to carbon pricing by 2027.
If the price of sustainable design and green materials remains stubbornly high, how can architects, designers, engineers and developers green an industry while keeping costs low?
Traditional Barriers To Sustainability
For now, Dubai’s construction marvel remains an outlier for what the combined powers of AI and the construction industry can achieve. Many developers still think of sustainability as a cost center, multiplying considerations for developers that add time and increase the budgets of projects. The materials themselves are also often more costly.
This means that despite the potential for long-term savings and higher returns, in many cost-benefit analyses, sustainability measures are hard to justify.
There is also a fundamental misunderstanding of the pathways available to reduce global warming emissions associated with the production, processing, energy and materials used in a building. These emissions, known as the embodied carbon of a construction project, are typically addressed by simply substituting “gray” with “green” building materials and optimizing for better energy use with more efficient lighting and alternative systems for heating, ventilation and cooling.
However, using new AI capabilities can allow architects and engineers to embed efficiency in the design phase to ensure that space is used efficiently and buildings are not over-engineered. This can reduce the environmental impact of construction and improve the operational energy efficiency of a building before anyone sets foot on a jobsite.
How AI Lowers Costs While Cutting Carbon
With design optimization through GenAI slashing development times, providing ideal planning and improvement of construction sequencing and simultaneously creating the most efficient pathways for construction while reducing costly rework, automation can enable sustainable practices at a fraction of the cost. These systems are ready to use, and their adoption is not tied to the physical costs of goods.
Tariffs and protectionism are pushing the costs of construction materials higher. Using design tools to create more efficient designs that reduce material consumption wherever possible is more than a luxury; it’s a necessity for building.
AI-Driven Design Optimization
Engineering design automation platforms that leverage machine learning can reduce material requirements by as much as 80% in manufacturing while maintaining performance. These systems can evaluate hundreds of design iterations overnight, identifying optimal solutions human engineers might never discover.
The same is true for construction. A Stanford researcher using specialized AI tools to optimize the construction of multistory commercial steel buildings estimated that they would reduce material costs between 9% and 20%. Design and structural optimization tools could achieve 19% to 46% embodied carbon reduction at cost premiums below 1%, according to a July 2021 report from nonprofit energy efficiency advocacy group RMI.
Material Innovation Through Predictive Analytics
Meanwhile, advanced generative design systems can enable the exploration of alternative materials based on performance criteria, cost and carbon impact. Since GenAI can present multiple solutions, engineers can evaluate different approaches to optimize sustainability and cost simultaneously. Cutting-edge platforms incorporate simulation engines that can accurately predict how different structural and electrical systems perform.
For instance, an apartment building using AI-optimized material substitutions achieved a 74% decrease in embodied energy while reducing costs by 30%, according to a case study cited by the AIA.
Construction Sequencing
Next-generation software can provide seamless integration between modeling, analysis and documentation—eliminating the traditional silos that create material waste.
These platforms automate the tedious processes for MEP systems design, where intelligent automation can route services with minimal material usage while avoiding clashes between different stakeholders.
During the Museum of the Future project, BIM technology reduced rework on-site by 65% and improved productivity by 50%.
The Path Forward
AI-enhanced design represents the future of sustainability in construction.
These design automation and generative tools have the power to bring what was once a bespoke solution available only to marquee developers into the hands of construction projects of all sizes. These platforms can ensure that design optimization translates to real-world sustainability. In practices like mechanical and electrical design engineering, as well as plumbing, this could mean an end to the rework that contributes to wasted materials and adds costs.
As regulatory mandates intensify and financing increasingly favors sustainability, expect the companies that embrace AI tools to have a competitive advantage. The question is no longer whether the industry can afford to build sustainably but whether it can afford not to embrace the technologies that make sustainability economically advantageous.
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