top of page
  • Staff Writer

AI's role in a greener built world: potential to offset entire US carbon footprint by 2030



Pi Labs, a global proptech venture capital firm, has published a research report titled "Sustainably Intelligent: AI for a Greener Built World," with fresh insights into how artificial intelligence can contribute to reducing carbon emissions in the built environment.


The report notes that widespread adoption of just four AI use cases could potentially avoid 5.81 to 6.46 gigatonnes of CO2-equivalent greenhouse gas emissions annually by 2030.


Pi Labs asserts that this reduction could effectively counterbalance the entire yearly carbon footprint of the United States, the world's second-largest emitter of greenhouse gases, as of 2022.


Following an examination of 68 sustainability-focused AI use cases throughout the value chain, specific areas were selected for detailed analysis using both proprietary and public data.


These include optimising raw material inputs through generative design, mitigating construction rework with 3D AI analytics, enhancing building energy efficiency with AI-enabled smart building technology, and managing demolition waste through AI-enabled waste material analysis.


Luke Graham, Head of Research of Pi Labs, said: “With the built world already falling behind on climate targets, we are pleased to share that the findings of our report indicate that AI is set to have a transformative impact on carbon reductions.


“According to venture funding data from 2023, there is already significant investor interest in AI driven green solutions aimed at the built environment, however there is the potential to drive this figure up yet further with a clearer understanding of the positive climate impact and growth potential of these technologies.


"The good news is that the pace of AI innovation being achieved since the launch of ChatGPT in late-2022 can be put towards significant climate change mitigation by 2030 and as always, the early adopters within the real estate world are set to benefit the most.”


A report at the tail end of last year, from JLL, a provider of real estate and investment management services, highlighted the potenetially massive impact that artificial intelligence is widely expected to have on real estate over the next few years.


But it’s just the latest in a long line of technologies that have reshaped the industry in recent decades, from making buildings more energy efficient to managing spaces in the hybrid-work age.


These proptech innovations place the increasing adoption of AI in real estate as more of an evolution than a revolution, said Yuehan Wang, global research associate and lead for the JLL Global Technology Research Program.

It noted that with over 500 companies globally currently developing AI-powered services relevant to real estate, AI is set to wield the biggest influence.


In fact, the total capital raised to fund AI-powered Proptech reached $4 billion globally in 2022 – twice that raised in 2021, according to venture capital and private equity research firm PitchBook.


“AI technology is also used to analyse data from the building management system to understand the performance of the equipment in that building, identifying clearly what might need to be changed or maintained,” said Carolyn Trickett, Growth Principal at JLL Spark Global Ventures, the corporate venture arm of JLL.


Another strength of AI is its ability to rapidly analyse large amounts of data, even from different data streams, something that can more efficiently inform management decisions.


AI can also work 24/7, and generative AI, which uses advanced algorithms to generate content like the answer to customer queries, can be trained to respond to out-of-hours queries, increasing satisfaction from existing tenants, or the potential conversation rate of prospective ones.


While AI technology and its capabilities are still in their infancy, there are some legitimate concerns that any early adopter needs to consider.


“The regulation landscape for AI isn’t moving quite as fast as the technology,” Wang said, “So you should consider potential risks in cybersecurity or data security when considering implementation.”


3 views0 comments

Comments


bottom of page