Insight - AI and sustainability

On November 25, 2025, the RICS hosted a webinar on AI and sustainability featuring four industry experts. This is a summary of the discussion.

Overview

The panel described how AI is driving a rapid, values-based transformation in real estate, shifting focus to growth and sustainability by integrating financial and technical data to predict climate risk and automate retrofit planning. This requires humans to transition from knowledge workers to wisdom workers, applying judgment and ethical context to AI's output.

📈 The Impact and Adoption of AI

The current AI trend is an exciting time for the industry, offering benefits for solving complex problems. It's crucial, however, to complement AI tools with deep expertise and reliable data to ensure robust and useful output.

• Rapid Adoption: The adoption of AI is growing exponentially, with 88% of investors currently running AI pilots, a massive increase from 5% just two years prior.

• Focus Shift: Initially focused on operational efficiency and cost reduction, the focus has shifted to growth-oriented themes such as investment strategy and differentiation.

• Three Thematics of AI Evolution (3-5 years):

  1. Process Optimisation: Doing existing tasks better and more efficiently (current primary focus).

  2. Workflow Redesign: Delivering desired outcomes fundamentally differently, enabling new services.

  3. Paradigm Shift: Profound change in how real estate is used, driven by market volatility (e.g., shorter leases, changing investment models).

• The Volatility Context: This rapid change is occurring as 78% of office product needs significant investment, further compounding volatility.

  
  

🔗 Convergence of Data and Decision-Making

A major theme is the convergence of different data sets, facilitated by AI tools:

• Data Integration: The next 3-5 years will see the convergence of financial data (e.g., ROI) and technical/sustainability data (e.g., carbon emissions) into single platforms.

• Real-time Modelling: This integration will allow for real-time updates to asset valuation models based on retrofit changes.

• Evidence-Based Leadership: This shift requires leaders to become data interpreters, asking the right questions of AI and challenging the "black box" output, moving from intuition-based to evidence-based decision-making.

• Valuation Shift: AI helps bridge the gap where historic data (used in traditional valuations) struggles to capture forward-looking value created by sustainable investments, which are crucial as markets shift from "downhill skiing" (relying on cap rate compression) to "cross-country skiing" (requiring a more active approach).

  
  

🛡️ AI for Climate Risk and Retrofit Planning

AI is fundamentally changing how climate-related risks and retrofit opportunities are assessed:

• Static to Dynamic Risk Assessment: Moving from using historical data ("what happened last year") to predicting future scenarios ("when will this asset be stranded").

• Two Key Risk Areas:

  1. Physical Risk: Using machine learning and geospatial analytics to map portfolios against climate models, predicting highly granular risks like flood depths and heat stress 10-20 years out.

  2. Transition Risk: Ingesting regulatory data and energy price forecasts to model exactly when an asset will become financially unviable ("brown"), allowing for precise CapEx planning.

• Retrofit Automation: Research suggests 65% of the retrofit process can be automated through existing technologies like image recognition and data modelling, covering:

  1. Portfolio prioritisation.

  2. Energy audit.

  3. Construction management.

  4. Data sharing and optimisation.

     
     

👤 The Human Role in an AI World

The speakers emphasise that AI will be an augmenting technology that requires a "human in the loop":

• Wisdom Workers: Humans will transition from mere knowledge workers to wisdom workers, applying their values (such as sustainability, long-term investing, and intergenerational equity) and judgment to AI's output.

• Head of Sustainability Role: This role is evolving to become a pioneer in transformation, ensuring AI deployment aligns with organisational values and focusing the conversation beyond mere process optimisation.

• Human Filter: For decarbonisation and retrofits, a human filter is essential to verify AI suggestions against on-site realities, review CapEx/financial information, and unlearn old practices.

• Wider Investment Context: While AI tools can assess a decarbonisation project's internal rate of return (project IRR), the human element is needed to place that investment in the context of the broader asset investment strategy to unlock more capital and greater impact.

Sustainable investments in real estate will create value and demand, driven by stringent decarbonisation targets and accelerated by AI-powered tools.

💰 Future-Proofing Assets for Value Creation

Sustainable investment is essential for protecting and creating asset value, especially in markets like London offices, by meeting tenant demand and anticipating future regulatory changes.

• Proactive Compliance: Assets must be future-proofed against increasingly stringent regulations (e.g., the EU target of a 70% reduction in carbon by 2035).

• Mitigating Price Risk: For core funds with a 10-year horizon (e.g., buying in 2025, exiting in 2035), failing to underwrite for future regulations creates a real risk of price chipping on exit. This risk extends even to shorter-hold periods (e.g., 3 years for value-add) as the ultimate buyer (core/core-plus) must consider the long-term liability.

• Occupier Demand: Leading occupiers are rapidly integrating decarbonisation into their real estate planning, with some global financial services firms treating a building's carbon performance on par with cost when selecting a site.

  
  

🏢 Occupier Engagement and Portfolio Planning

AI tools are facilitating a significant shift in how tenants manage their space and capital expenditures (CapEx).

• Accelerated Portfolio Planning: Occupiers are now conducting portfolio assessments every 6 months, rather than the traditional 5–10 years, combining decarbonisation targets with space rationalisation.

• CapEx Optimisation: A top priority for occupiers is managing the significant CapEx requirements to meet their 2030 targets (which fall within their current leases). An integrated portfolio approach is the only way to manage these prohibitive costs.

• Differentiated Engagement: In operational real estate (e.g., student accommodation), landlords are integrating decarbonisation behaviours into the wider customer experience by linking sustainability incentives to services and local business partnerships via technology.

  
  

📊 Data-Driven Trust and Reporting

AI strengthens sustainability reporting by establishing a verifiable, data-driven discipline similar to financial accounting.

• Verification, Not Declaration: Trust is built through verification, not declaration. AI tools provide a transparent, digital, auditable trail for all sustainability data.

• Evidence-Based Reporting: Instead of just reporting a final number, intelligent tools allow investors/tenants to drill down into the source data (e.g., meter readings, utility bills).

• Shifting Metrics: Investors demand transparency into specific, hard metrics such as Energy Use Intensity and Carbon Intensity per square meter, moving beyond general sustainability statements.

• Real-Time Tracking: AI enables real-time tracking of metrics, providing stakeholders with confidence that strategies are on track and ensuring any "green premium" paid is backed by physical and financial reality.

  
  

🚀 Adapting to Volatility and AI Adoption

Organisations need to be adaptive ("bouncing forwards") rather than just resilient ("bouncing back").

• The Evolving Human Role: AI augments the human, enabling professionals to focus on insight and critical decisions ("the so what") rather than manual data processing. For instance, using AI to benchmark home builders' sustainability credentials enabled the team to deliver higher-quality, more consistent results while shifting their time from analysis.

• Accessibility and Global Adoption: AI is an accessible, democratising technology. Adoption rates are high in diverse regions like India, where there's an openness to view it as a tool for societal change and entrepreneurialism.

• Practical Steps for Organisations:

  • Sonny Masero: Lean into understanding AI; don't let hype or ego prevent experimentation.

  • Paul Stepan: Jump in and simplify it; immediately start building a code of practice (rules of the game) for the organisation.

  • Dr Yishuang Xu: For smaller firms, focus on collaboration and standardisation; use industrial-grade SaaS platforms for data aggregation and benchmarking rather than building custom AI.

Note: Access to the webinar recording is free for members with an active RICS support pack subscription.