1. What challenges does AI create for commercial real estate, especially regarding data management and security?
Any new technology has implementation hurdles, like upgrading IT infrastructure and budgets – not just for purchase and setup, but also ongoing usage costs. The more interesting challenge is people.
Effective AI use rests on two things:
• Overcoming fear: Many people think AI will replace their jobs, but in reality, it will make their jobs easier. AI can tackle repetitive, high-volume tasks and help leverage data to drive decision-making. Successful companies will show staff how AI can increase productivity.
• Set expectations of responsibility: AI education must increase understanding, set guidelines, and discuss caveats – setting the stage for ethical use.
AI tools don’t always surface data sources, so users must know best practices for data privacy and security as well as IP protection. Otherwise, AI outputs could include your content and IP from other companies, elevating legal and security risks. Organizations must make guidelines to ensure accountable AI-enabled solutions.
For example, MRI Software’s responsible AI framework helps us avoid ethical dilemmas, bias, breaches, inaccuracies, and liability.
2. How can AI technology and data enhance real estate client experiences and operational efficiency?
AI excels at making sense of massive volumes of data. It performs wide-ranging analyses, delivering reports that are too cost- and time-prohibitive for humans, so they can make smarter decisions.
Lease abstraction drives the biggest time savings and value creation gains. AI-powered tools like MRI Contract Intelligence can turn unstructured data from complex lease documents into structured, machine-readable text, simplifying extraction, digital querying, and use in other applications. Similarly, AI lets users make data queries without requiring technical know-how. For example, MRI Agora Insights helps management teams find information without knowing exact field names – and the output is trustworthy because it’s based on the company’s data sources.
There’s also finance and investing. By analyzing historical data and market trends, AI can estimate future cash flows, revenues, and spending to enhance budgeting. AI tools can predict asset values based on location, amenities, historical prices, and market trends, enabling more accurate valuations.
These capabilities aren’t limited to recent data. Organizations may have decades of historical property, lease, and contract data that AI can use to fuel more accurate predictive modeling and forecasting to uncover efficiencies, test strategies, and unlock portfolio value.
3. What trends will impact industry stakeholders the most in the next few years? How should they adapt to capitalize on these trends?
AI adoption. Deloitte found that real estate firms have invested $7.2B in AI. Still, most organizations rely on some type of legacy technology. AI investment isn’t slowing down, and firms that don’t adopt it will be overtaken by more productive, efficient ones.
The big challenge for owners, operators, and investors will be determining the right AI approach: buying an existing application, integrating third-party models via APIs, or developing an in-house system. The decision requires balancing budget and timing limitations with data security and IP infringement risks.
Most AI investment now goes to transaction support – creating property listings, financing and valuation, and data analytics. We’ll see growth in complex tasks like lease and contract abstraction, energy and facilities management, and portfolio decision support.
Changing interest rates: Lower interest rates will help organizations more easily finance new deals. The market will improve, creating new opportunities to expand portfolios, refinance current holdings, or replace assets with ones that better fit their strategies.
As the market evolves, owners and investors need automated portfolio solutions to create more value. For example, MRI Investment Central has tools that automatically track asset values across portfolios and calculate the optimal value for each property.
Data democratization. All organizations are pushing teams to be more efficient and effective. That requires performance benchmarking and data access. Firms must make sources accessible to avoid overwhelming IT with requests for data, analysis, and reporting.
Effective organizations will connect data sources and systems with platforms like MRI AgoraTM. Stakeholders across the organization can access the data they need to improve performance. A centralized system creates a unified source of truth to align all teams. MRI Agora Insights extends this concept by connecting teams across the organization with advanced data analysis.
Energy efficiency. Rising energy costs and climate change will drive more laws like New York City’s Local Law 97. Commercial buildings must meet stricter energy and emission targets or face increasing fines, requiring modernization of infrastructure and equipment.
Before making large investments, organizations should accurately measure how and where they currently use energy. Research shows buildings waste as much as 30% of their energy. When wasteful areas are fixed first, organizations can optimize spending to make the biggest impact on emissions and energy efficiency.
AI-driven systems like MRI Energy collect data from sensors, smart meters, and utility bills so stakeholders truly understand current energy use. They can analyze incoming energy data, quickly spot usage anomalies, and alert the appropriate teams to act quickly.
Foot traffic data can uncover further savings. Solutions like MRI OnLocation for Footfall Analytics can show when spaces aren’t used, such as when tenants work remotely. Lighting, HVAC, and other equipment in unused areas can be reduced on those days, lowering energy use, emissions, and utility costs.
