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.

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.

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. 

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:

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.