As real estate owners face mounting pressure to decarbonize, protect asset values, and remain capital efficient, a core challenge has emerged: navigating the financial implications of net zero. It’s not simply a question of compliance. It’s a decision‑making crisis—one that cuts across underwriting, asset management, ESG, and development. For many, it has become the industry’s single biggest risk. But paradoxically, it’s also the sector’s largest untapped source of value creation. And for the first time, AI offers the tools to solve it.
From Risk to Opportunity: The Financial Stakes in the US and Europe
More than three‑quarters of real estate assets globally are not on track to meet net zero trajectories. In the US, legislation such as New York City’s Local Law 97 mandates strict greenhouse gas emissions limits for large buildings—those over 25,000 square feet—starting in the 2024–2029 compliance period. Buildings that exceed emissions caps face significant fines per ton of CO₂ equivalents over their limit. Non‑compliance thus risks both penalty exposure and long‑term valuation decline¹.
At the same time, decarbonization—or “green capex” in US parlance—has become a strong financial driver. Low‑carbon assets are already commanding rent premiums of up to 15%, enjoying reduced operating costs, improved net operating income (NOI), more favorable financing, and lower risk discounts². The opportunity is real. But complexity remains high—and delay is very costly.
Why Complexity Has Never Been Solved—Until Now
Meeting green capex commitments without eroding value requires solving multiple overlapping challenges:
- Integrating asset‑level specificity with portfolio‑level strategy
- Managing the full building lifecycle, from underwriting and acquisitions through ESG, asset operations, retrofits, and development
- Reflecting differences by asset class, geography, regulation, and tenant profile
- Reflecting and handling hundreds of data points for a single building: components & systems, CO₂ emissions, energy intensity (EUI), local infrastructure (for example, district heating), climate forecasts, construction cost trends, subsidies/incentives, stakeholder and investor constraints, budget limits and many more.
- Overcoming organizational silos, fragmented decision‑making, lack of unified data, and absence of a single source of truth
Most digital renovation tools entering the market still rely on simplified benchmarks: they may flag what might be needed for one building but lack the depth, scenario logic, or portfolio‑scale reliability to guide capital allocation decisions across many assets.
Why AI Finally Makes a Strategic Difference
AI is not a black box—and expert input matters. When expert domain knowledge (engineering, finance, ESG, operations) is embedded in AI‑enabled workflows, models are grounded, interpretable, and calibrated to real operational constraints. AI doesn’t replace judgement—it amplifies it.
McKinsey’s research shows that using AI to optimize decarbonization and investment strategies can lead to up to a 100× increase in the pace and scale of decarbonization planning, compared to traditional audit‑by‑audit or spreadsheet approaches³. This dramatic uplift comes from rapid, automated scenario generation, building‑by‑building pathway plans, cost‑optimisation through equipment bulk procurement, and integration across data types (weather, energy, regulatory, financial).
The role of experts is central in validating AI outputs, adjusting assumptions, and making trade‑off decisions—not leaving them to pure algorithmic output. Together, this yields decision‑ready insight: which buildings to retrofit, which to hold or sell, when, and to what specification.
What’s in It for Owners and Asset Managers?
When decision‑makers apply AI and make the right decisions empowered by it, several value drivers can be unlocked:
- Rent premiums of up to 15% on buildings with high energy performance and ESG ratings
- 30‑50% reduction in green capex through smarter targeting of retrofit measures (e.g., prioritizing high return projects and energy efficiency measures, reflecting grid decarbonization)
- Lower cap rates due to reduced perceived risk and improved ESG credentials among tenants and investors
- Enhanced asset liquidity: certified, compliant assets trade more readily
- More favorable financing terms: access to green bonds, PACE/C‑PACE, sustainability‑linked loans
- Significant savings on consultant fees and internal resources; ability to manage larger portfolios with leaner teams and faster decision‑making
The critical thing is that these gains come not simply from owning AI tools, but from using them to drive better investment, capital allocation, and operational choices—ones that align financial return with regulatory, climate, and tenant pressures.
Key Success Factors to Overcome Inhibitors and Common Misbeliefs
Despite the promise, many hold back. Common misbeliefs include:
- That 100% data completeness is required before any meaningful action
- That green capex is purely a cost rather than a financial investment with return
- That AI is opaque or too technical and disconnected from operational reality
- That internal teams lack the capability to interpret AI outputs.
To counter these, asset managers must:
- Secure top‑down commitment: CEO/CFO/board must see AI and green capex strategy as intertwined with financial performance
- Ensure cross‑functional team collaboration: bringing together finance, sustainability, operations, development so assumptions and trade‑offs are realistic
- Begin with pilots on high‑impact assets, then scale based on learnings and improved data quality
- Choose tools that are transparent, scenario‑capable, audit‑facing, and able to allow expert intervention
In Europe, the ULI report warns that €1.5 trillion of property is at risk of devaluation without deep retrofits to meet evolving energy/carbon standards⁴. For many European portfolios, waiting even a few years means locking in obsolescence costs. A quote worth noting: “Investors will be seeking to avoid assets at risk of stranding, or incurring penalties for failing to comply with tightening legislation⁵”. That urgency applies in the US as well.
Conclusion: Waiting Is Costly, Acting Is Strategic
Decarbonization is now a board-level financial issue. The threat of value erosion through stranding or regulatory penalties is matched by the upside of NOI growth, asset appreciation, and financing advantages. US regulation such as New York’s Local Law 97 makes delaying action not just risky but expensive. Similarly, tightening legislation in Europe—like France’s Décret Tertiaire, which imposes binding energy reduction targets and reporting obligations—makes the cost of inaction steep and visible.
This imperative extends beyond asset managers and property owners. Advisors and consultants must also adopt AI to better serve clients facing capital planning challenges. Banks and insurers—who must now stress test real estate loan portfolios—can turn this into a value-added service for borrowers while enabling green finance offerings. Facility managers, with deep knowledge of building systems, are well positioned to apply AI in producing early-stage diagnostics and retrofit roadmaps. Even private equity firms, REITs, and family offices stand to gain by embedding AI into their investment, due diligence, and asset optimization workflows.
For real estate firms seeking competitive advantage, embracing AI isn’t optional. It’s essential. The firms that act now—leveraging expert-guided AI, integrating data, making better decisions—stand to unlock outsized returns: higher NOI, stronger valuations, reduced risk. Waiting? That’s an expensive strategy.
References & Quotes
- New York City Local Law 97: Emission limits and penalties for large buildings
https://www.nyc.gov/site/buildings/codes/ll97-greenhouse-gas-emissions-reductions.page
- JLL (2024), “Buildings: Value vs Energy Performance”, Global Research Report
https://www.jll.com/en/trends-and-insights/research/buildings-value-vs-energy-performance - McKinsey & Company (2023), “A new way to decarbonize buildings can lower emissions—profitably”, Brodie Boland, Daniel Cramer, et al.
https://www.mckinsey.com/industries/real-estate/our-insights/a-new-way-to-decarbonize-buildings-can-lower-emissions-profitably
- ULI Europe – Net Zero Imperative: €1.5 trillion at risk of devaluation without deep retrofits
https://realassetinsight.com/2025/05/13/ulis-seven-principles-to-avoid-the-risk-of-stranded-assets/ - Savills Commentary: Stranding risks rising across Europe amid tightening regulation
https://www.savills.com/insight-and-opinion/savills-news/336572-0/as-legislation-deadlines-loom–europe-risks-threat-of-stranded-office-assets - CRREM (2023), Stranding Risk & Carbon Pathways: Real Estate Decarbonization Models
https://www.crrem.eu/wp-content/uploads/2023/05/CRREM-Stranding-Value-Risk-Model.pdf - ZIA & EY (2025), Digitalisierungsstudie 2025: Immobilienwirtschaft zwischen Innovation und Realität
https://zia-deutschland.de/wp-content/uploads/2025/09/20250908_Digitalisierungsstudie-2025_ZIA-und-EY.pdf
