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.

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: 

• 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.
• 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.
• 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 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.

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.

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.