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By 2030, Artificial Intelligence (AI) 鈥� or computer systems that can perform tasks typically requiring human intelligence 鈥� is forecast to .

In this article, Max Beard, Associate, Innovation Architect, and Flora Harley, Head of ESG Research, highlights some of the benefits and advancements in AI could have for ESG within the real estate sector, and why investors, developers and occupiers must keep up or risk being left behind.

But first, what does AI actually mean?

As mentioned above, AI is a machine's ability to perform the cognitive functions we associate with the human mind, such as perceiving, reasoning, learning and interacting.

Although there are many different types and definitions of AI, key areas include Machine Learning (ML), where systems learn from data and make predictions without explicit programming; Natural Language Processing (NLP), which involves interaction between computers and language, enabling machines to interpret or generate meaningful text or speech; Generative AI, such as ChatGPT, and Predictive Analytics, which uses algorithms and ML to predict outcomes based on historical data.   

These areas and methodologies often overlap, working together to create more advanced AI systems across various industries.

Why is AI crucial in today鈥檚 real estate market?

AI has the potential to transform every stage of an asset鈥檚 lifecycle, from design and construction, compliance, occupier experience, and ongoing asset management. By investing in AI technologies, real estate landlords and developers have a huge opportunity to benefit from improved data-led decision making, leading to improved efficiencies, cost savings and better sustainability outcomes.

How can AI help optimise building usage and improve ESG management?

Real estate is an asset-intensive industry, and as competition and investor demand for data grows, building owners must adapt to stay ahead. AI has the potential to increase property performance and appeal, through energy optimisation, compliance with evolving regulations, and by ensuring they can meet the increasing demand for sustainable buildings.

Some of the potential uses and implementations for AI within the context of ESG include:

Optimised building use

AI can analyse building operations to optimise and reduce energy consumption. For example, using sensors means HVAC and lighting systems can be fine-tuned to be made more resource efficient. By expediting the collection and analysis of data, in addition to the automation of systems, AI can potentially help to lower costs and reduce emissions, not only helping operational performance but advancing towards zeroes and net zero targets.

Streamlined certification processes

AI also helps with ESG standards and certifications like BREEAM or LEED, by streamlining data collection, ensuring accuracy, and helping to meet certification criteria more efficiently. This may lead to a greater uptake in schemes such as these as a result, and our research has found rental and associated with BREEAM certifications in central London offices.

Predictive maintenance

Taking a proactive approach to asset management using predictive analytics can reduce repair time, minimise building downtime, extend asset life, protect reputation, and boost tenant satisfaction.

Standardised data collection

With regulations around ESG tightening, real estate owners need to collate and present more data than ever before, and AI provides a way to streamline and standardise the data collection process, reducing the burden of compliance. Manually collecting data, particularly across many different assets, can be complex, prone to errors, and hard to digest, but AI can automatically gather and analyse relevant data across multiple systems such as energy use, tenant occupancy, and maintenance schedules. The information can be analysed more easily, and actionable steps put in place.

For landlords looking to sell, AI can ensure the data is accurate, comprehensive, and presented in a standardised format. This makes it easier for buyers to assess the building鈥檚 ESG performance, leading to faster transactions and potentially higher sales value due to the building鈥檚 sustainability credentials.

Improved communication strategies

AI-driven tools such as NLP can be used to analyse tenant satisfaction and well-being, social sentiment, and provide insights into community needs and concerns. Real estate projects can be assessed for their accessibility features, ensuring the project aligns with inclusivity standards.

When will we see measurable impacts on sustainability as a result of AI in the real estate industry?

AI has already begun to shape the future of the built environment, especially in terms of sustainability and compliance, but its full potential will unfold over the next few years. By automating time-consuming tasks like data collection and analysis, AI frees up human resources to focus on more strategic decision-making. Faster decision cycles, more accurate reporting, and optimised property management practices will allow real estate owners and developers to stay competitive and meet growing demands for ESG accountability.

Our Innovation Team

Working in partnership with clients and colleagues, we use technology to identify and address the challenges facing the real estate sector in 2025. We determine, develop and implement streamlined solutions that drive value and efficiency.

Our PropTech and Innovation team are experts from a variety of professional backgrounds, including technology, design, and business strategy. Together with the wider ESG Consultancy team, we are ready to assist clients in understanding how the use of AI can help support their ESG objectives.