Last week, I moderated a panel at the IMN ESG Conference in Dana Point “How Commercial Real Estate Leaders Are Using AI to Take Action on Their Decarbonization Goals,” one thing was clear: the future of sustainable real estate is intelligent, data-driven, and already in motion.

We heard from senior sustainability leaders and tech innovators about how AI is transforming sustainability from aspiration to measurable impact for commercial real estate assets and portfolios.

Commercial real estate (CRE) is at a critical inflection point. The sector—long seen as a major contributor to global carbon emissions—is now under unprecedented pressure to decarbonize. But as ESG mandates tighten and climate risks mount, traditional approaches to carbon reduction are proving too slow, too siloed, and too manual to meet the moment. Enter artificial intelligence (AI): not just a buzzword, but a real tool for measurable impact.

Across the industry, forward-thinking building owners, asset managers and sustainability leaders are turning to AI to accelerate their decarbonization strategies—transforming carbon tracking, capital planning, compliance and lease renewals into streamlined, data-driven processes.

How can you use AI to achieve your climate goals for your real estate assets and portfolios?  Following are some tips on how to CRE leaders are using AI to accelerate change.

1. AI in Carbon Tracking: From Manual Spreadsheets to Automated Precision

Historically, tracking emissions across a real estate portfolio has been time-consuming and error-prone, plagued by fragmented data sources—from utility bills to BMS logs to third-party benchmarking and data management tools.

Now, AI is enabling:

• Automated data integration: Platforms powered by machine learning can pull data from utility meters, ESG reporting systems (e.g., GRESB, ENERGY STAR), IoT sensors, and energy management software—standardizing it in real time.
• Granular emissions measurement: AI models can allocate emissions down to specific buildings, floors, systems, and even tenants, enabling a precise understanding of carbon hotspots.
• Predictive emissions baselining: By analyzing historical usage patterns and external factors like weather or occupancy, AI can forecast emissions trends and pinpoint outliers for intervention.

Result: faster, more accurate reporting—and stronger foundations for action.

2. Smarter Retrofits: AI-Powered Capital Planning

Decarbonizing an asset or portfolio typically involves complex trade-offs: Which HVAC system should be replaced first? Will rooftop solar deliver ROI faster than insulation upgrades? What sequence of retrofits achieves the best emissions cuts per dollar?

AI is reshaping this decision-making process by:

• Generating retrofit roadmaps: AI tools analyze asset condition, utility usage, climate zone, and local incentive programs to recommend tailored retrofit strategies.
• Prioritizing by impact: Algorithms score upgrades based on factors like carbon abatement potential, payback period, tenant disruption, and regulatory urgency.
• Simulating outcomes: Building performance simulations powered by AI help visualize energy and emissions impacts pre- and post-intervention—minimizing risk in capital planning.

This shift enables more agile, targeted retrofit strategies—delivering savings in both carbon and capital. AI is transforming how capital projects are evaluated; what once required on-site engineers and labor-intensive assessments can now be done through desktop analysis. By quickly identifying the highest-impact opportunities, teams can prioritize upgrades more efficiently and cost-effectively than ever before.  Once a desktop analysis is completed, engineers can be employed to do a deeper analysis and perform ASHRAE Level two audits for a handful of assets instead of a whole portfolio.

3. Real-World Use Cases: From Pilots to Portfolio-Wide Impact

CRE firms are already seeing measurable results from AI-driven sustainability initiatives:

• Energy reductions of 10–30%: Portfolio-wide deployment of AI for HVAC and lighting optimization has led to significant efficiency gains—without sacrificing occupant comfort.
• Streamlined compliance reporting: AI has cut ESG reporting time by 50% or more for some asset managers by automating data collection, formatting, and submission for frameworks like LEED, GRESB, and local benchmarking ordinances.
• Cross-departmental collaboration: With AI-generated dashboards and insights, sustainability teams are aligning more effectively with asset managers, finance leaders, and facilities operations—turning ESG goals into enterprise-wide priorities.

4. Overcoming Data Challenges with AI

One of the most persistent obstacles in CRE decarbonization is fragmented, analog, or incomplete data. Many buildings still rely on outdated systems or disconnected software tools, creating barriers to insight.

AI is helping CRE firms overcome these hurdles by:

• Ingesting unstructured data: Natural language processing (NLP) can read scanned utility bills, equipment specs, or lease clauses and convert them into structured, usable data.
• Creating a digital backbone: AI platforms act as centralized data hubs, unifying inputs from disparate systems—BMS, CMMS, ERP, utility APIs—into a single source of truth.
• Navigating regulatory complexity: AI engines can stay up to date with evolving carbon regulations and automate compliance workflows based on asset-specific requirements.

5. AI as a Climate Accelerant in Commercial Real Estate

The promise of AI extends beyond optimization. When used strategically, AI can fundamentally shift how CRE firms approach decarbonization:

• Accelerating retrofits: By identifying cost-effective pathways to decarbonization, AI reduces the time from diagnosis to execution.
• Unlocking capital efficiencies: Better forecasting and prioritization lead to smarter allocation of capex, reducing stranded asset risk and boosting ROI.
• Mitigating climate risk: AI tools can assess physical and transition risks under different climate scenarios—informing portfolio resilience strategies.
• Driving net-zero alignment: With real-time emissions visibility, firms can track progress toward net-zero targets, adjust course quickly, and credibly communicate impact to investors and regulators.

Conclusion: From Hype to Action

AI isn’t a silver bullet—but it is a powerful enabler. For CRE leaders facing growing decarbonization demands, AI offers speed, scale, and precision that manual systems simply can’t match. The firms that succeed won’t just deploy AI tools—they’ll embed them into decision-making across the organization.

In the race to net zero, commercial real estate can’t afford to wait. With AI, the path to action is clearer—and faster—than ever before.