Streamline Sustainable Asset Enhancement with AI

Key Highlights

• JLL research shows that current AI capabilities can potentially optimize 65% of sustainable asset improvement-related tasks through increasing accuracy and speed, streamlining processes and allowing for better data management and retention.
• Leveraging AI-powered technology empowers owners and investors to take a more informed, data-driven approach on their overall asset enhancement and energy retrofit strategy, allowing them to navigate uncertainties in cost-effectiveness and payback periods.
• AI-powered technology could add the most value at four key strategic points in the asset enhancement process: portfolio prioritization, energy audit and modeling, construction management, and stakeholder data sharing. 
• Investors and building owners can take proactive steps for AI integration by defining AI objectives and priorities, assessing organizational readiness, analyzing providers and evaluating the best approach.

How can AI streamline the entire life cycle of sustainable asset improvement projects - from asset selection to audits, delivery and beyond? In our latest research, we set out to provide a holistic view of sustainable enhancements across different areas of commercial real estate operations and outline practical steps for decision-makers to harness this evolving technology and enable decarbonization at scale. In this article, we use the term “retrofit” broadly to encompass sustainable asset improvement projects that extend beyond traditional energy-efficiency upgrades.

A longstanding challenge

Asset enhancements have long helped real estate investors and building owners to increase values, attract quality tenants and comply with regulations. Sustainable asset enhancement, typically delivered through retrofitting, prioritizes enhancing energy efficiency, decarbonization and sustainability performances. It targets three critical real estate objectives: (1) future-proofing existing assets to prevent “brown discount” in value, (2) reducing buildings’ operational costs, and (3) achieving decarbonization.

According to JLL research, light to medium energy retrofits alone can unlock between 10% and 40% in energy savings, translating to $0.49 to $1.94 per square foot savings on average. However, despite this potential, these actions are not being implemented at the scale required; retrofit rates need to triple to meet critical decarbonization targets and achieve net-zero emissions by 2050, as outlined in the Paris Agreement. At the same time, the deterioration of building components and equipment poses a real threat, not least to asset values, with an estimated 65% of office buildings at risk of being stranded by 2030. 

So why are we still not improving the resiliency of our buildings? What is preventing this from being undertaken at scale? 

In working with industry experts, we have identified three common hurdles:
 

1. High stakes: The first and most important reason is the capital-intensive nature of some of these projects. The high capex required means securing finance and gaining stakeholder buy-in are major challenges, especially for deep retrofits. With cost effectiveness being the biggest concern, owners and investors can’t afford to make mistakes in these decisions and tend to act with high discretion.
   
2. Complexity in decision-making: Successful asset enhancement projects involve answering a series of difficult questions, such as which buildings within a portfolio will yield the best ROI from retrofits, what are the most financially viable scopes and timings, and how to plan these projects to optimize cost-efficiency and minimize disruptions.
3. Inadequate data and tools: The lack of consistent data collection and information retention into digital formats means most retrofit projects fail to benefit from data-driven insights and past learnings. Without high-quality data and effective tools, inadequate planning leads to wasted capital and less favorable results in the execution process.

The opportunities for AI-powered technology

The successful planning, management and monitoring of asset enhancement projects involves a multitude of tasks. Mapping these tasks against current AI capabilities and product availability reveals clear opportunities for integrating AI for innovative and effective delivery of sustainable asset enhancements at scale.

Contrary to the common misconception that AI will take over large segments of work and create entirely new business models, its most profound impact is less glamorous but crucial, achieved through multiple small-scale cumulative improvements at different strategic points. Through detailed expert reviews, JLL found that current AI capabilities, such as image recognition, data modeling and text generation, could enhance the effectiveness of an estimated 65% of all tasks in the sustainable asset enhancement process by increasing accuracy and speed, streamlining processes and allowing for better data management and retention.

Among these, four key strategic points stand out where AI-powered technologies could add the most value.

1. Portfolio Prioritization: select the right building(s), timing and scope of retrofits

Recent findings from JLL’s Asset Enhancement Initiatives Survey reveal that understanding the payback period and securing project funding are the largest barriers to undertaking asset enhancement projects. Retrofits, particularly medium to deep retrofits, are so capital-intensive that building owners and investors tend to act with the highest discretion.

However, most owners and investors lack a systematic approach to these projects. Large sums of capital are often committed based on individual building audit reports, without proper portfolio-level oversight. But building audits are not designed to analyze hundreds of properties simultaneously. Companies and experts need effective tools to align priorities - including target tenant preferences, sustainability goals, equipment replacement cycles, upcoming lease expiries, regulatory changes and investment requirements - to help develop a data-driven, costed, time-sequenced and actionable roadmap.

AI and tech solutions offer significant potential to address this strategic planning challenge:

Example AI-powered technology functions available:

With the help of AI-powered tech tools, portfolio-level retrofit planning can shift from an ad-hoc and fragmented process to one that is highly coordinated, precise and aligned with both financial and regulatory goals, thereby future-proofing assets effectively. 

These technologies are particularly effective in the absence of complete building audit data by bringing in external big data for reasonable benchmarks and assumptions. By leveraging capabilities such as data integration, interpolation, prediction and optimization, AI can help identify the most financially viable scope and timing for projects, as well as select and prioritize buildings within a portfolio to yield the best ROI. This step is crucial for securing funding and stakeholder buy-in. 

2. Building audit and energy modeling: creating efficiencies in time and quality

After initial portfolio-level scoping and prioritization, detailed building audits and accurate building-level energy modeling are essential for informing project implementation. As each building is unique, fully understanding a building’s energy use and predicting future patterns without the right tools is an arduous task. And without a comprehensive view on current and future potential energy consumption, the full cost-reduction impact remains unclear.

During the auditing process, auditors must collect, organize and interpret large volumes of information to extract useful insights on building conditions and energy consumption patterns. It is common to encounter issues like incomplete data and messy non-digitized documents. Then, after audits are completed, accurate energy consumption models need to be set up to formulate a detailed retrofit plan. However, the audit and modeling results are usually delivered in static PDF format, making it difficult for partnering stakeholders, such as ESG or finance teams, to integrate them into their workflows and annual capital planning cycles.

Due to the unique nature of every retrofit project, many tasks will require on-site presence; even so, there are an increasing number of AI tools that can create efficiencies in time and quality across these tasks.

Example AI-powered technology functions available:

AI-assisted audits offer direct benefits by reducing auditing time and increasing accuracy and data quality. AI-powered energy modeling enhances the ability to identify untapped energy saving opportunities and deliver monetary benefits in building operations. These AI-driven efficiency improvements can contribute to more buildings being audited and the creation and integration of more digital twins, a crucial factor in accelerating retrofits to align with net-zero targets. At the light retrofit end of the spectrum, AI-driven energy optimization products (like JLL’s Hank) can already offer cost-effective solutions with wide-ranging benefits and significant cost-savings.

3. Project execution: design, engineer and deliver the optimal asset sustainability improvement plan

The largest costs associated with asset enhancement projects are incurred during execution, encompassing detailed design, procurement of equipment and materials, construction and installation. The quality of work during this phase will determine the extent to which the core objectives – decarbonization and cost reduction in subsequent building operations – are realized.

Common challenges during project execution include limited design options due to time or budget constraints, rising costs of materials and labor, failing to adhere to the construction schedule and maintaining quality control throughout the process. These challenges pose risks of wasted capital and going over budget.

By using AI to optimize schedules and coordinate bulk purchases - especially if multiple buildings within a portfolio can be retrofitted simultaneously - projects can save significantly on materials, equipment and labor. AI can also enhance design, streamline procurement, optimize construction timelines, improve communication with contractors and even identify errors in invoices, ensuring the best results while minimizing costs.

Example AI-powered technology functions available:

Many of these tasks in the execution phase are consistent with other project types that involve design and construction. As a major segment in real estate technology, construction technologies offer the largest number of AI-powered products. There are opportunities to leverage off-the-shelf solutions.

4. Data and Communication: accumulate data and insights, bridge siloed stakeholders 

Traditionally, retrofits have been viewed as one-off, costly efforts with minimal knowledge accumulation. Without proper data retention and communication throughout the retrofit life cycle, decision-making continuously suffers from a lack of quality data, leading to ineffective planning and limited improvements over time.

Additionally, asset performance improvement projects typically involve various stakeholders from multiple specialist organizations. Centralizing and standardizing information exchanges has been challenging, resulting in isolated data and missed opportunities to gain collective insights.

By implementing AI, particularly the latest GenAI and LLM capabilities, information flow can be significantly streamlined, and best practices can be identified and replicated at scale. Updating retrofit results into a centralized database enhances future benchmarking and replaces rough assumptions with precise, data-driven insights, allowing experts to focus on adding value rather than on data collection and management. Accumulating high-quality data and insights establishes a valuable resource for broader applications in construction and decarbonization efforts.

Example AI-powered technology functions available:

More organized and structured data can yield coherent insights into retrofit processes, allowing owners and investors to continuously track ROI and develop a clearer understanding of payback periods. Enhanced communication between siloed stakeholder groups promotes effective information sharing, which is critical for project delivery and sustained post-completion performance. Most importantly, increased data availability will enhance the effectiveness of all previously discussed AI and technology use cases, bringing long-term cumulative benefits.

Actions to kickstart AI integration 

To enable retrofits at scale, systematic changes are necessary, such as prioritizing portfolio-level decarbonization planning and tracking long-term financial returns. These changes demand process innovation and advanced tools. As businesses shift from defense to offense in tackling the decarbonization challenge, we believe AI-powered technologies will empower building owners and investors to take a more strategic approach to tackling retrofits.

Considering available approaches to leverage AI, there are actions for building owners and investors to take now to kickstart AI integration:
 

• Understand your priorities (i.e., cost saving, time saving, meeting regulation, etc.) and define objectives for using AI to identify tools for maximum benefits.
• Assess the AI readiness of your organization. Identify gaps in data quality and availability. Move to digitize existing building information, lease time frames and other critical data on the portfolio level to enable decarbonization at scale.
• Conduct a detailed provider landscape scoping and evaluate the optimum approach to harvest AI capabilities: buy, build or partner.

AI will not directly solve all the challenges in sustainable asset enhancement and decarbonization, but by strategically integrating AI within project planning, management and implementation, building owners and investors can take a more informed approach to make a stronger business case for these enhancement initiatives, which is the premise of realizing net-zero and long-term return on investment.