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.

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.

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:

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.