In the world of commercial real estate, the current buzzword is uncertainty. This ranges from interest rates, tariffs, war, client risk, rising costs, mortgage rates, resources, a skilled workforce, new technologies and many other factors.
Modern software can help corral these disparate challenges into manageable data, but many companies are not using it to its full potential or do not offer the necessary training to make it most effective, according to a new survey of 600 CRE professionals by MRI Software.
Over the past six years, companies have become, if not blasé, at least accustomed to dealing with foggy outlooks: 81% said their organization had a greater risk tolerance for uncertainty and volatility than 12 months ago.
Some 47% said they are adjusting their forecasting models to account for greater risk, and 20% said they have incorporated a higher market risk tolerance into their strategic plans.
Others are updating their portfolios to reduce risk. Over 27% of respondents reported refinancing portfolio assets, 35% delayed acquisitions or paused new development, 25% sold assets and 11% divested their portfolios entirely.
Amidst all the uncertainty, software can help corporate decision-making. But the survey identified challenges to its effective use, including antiquated programs that make it hard to adopt AI, data integration difficulties and a lack of proper training.
Some 70% of respondents said dashboards have improved their business. The most common benefits named were access to real-time data (17%), standardization of data (14%), better data aggregation (12%), improved strategic planning (10%), faster decision making (7%), better outcomes or performance (6%) or other (4%).
"Most concerning are the respondents who shared comments that dashboards and visualizations aren't accessible or go unused. Companies that want to get the most value from their technology will need to address internal blockades keeping their teams from realizing the benefits of these tools," MRI stated.
The survey results revealed a gap between what these tools can do and how they are actually used. Of the respondents, 55% used data analytics for financial analysis, 54% for forecasting, 50% for operational analysis, 41% for real-time decision making, 32% for strategic development, 11% for scenario testing, while 17% said it did not apply to their role.
"With so many respondents focused on daily operations rather than strategic decisions, the technology may not be living up to its full potential. For example, scenario testing – seeing how different variables affect strategy outcomes – is being used by only 20% of executives, and very little by other groups," the report commented.
"Analytics can do much more than summarize data. CRE organizations that unlock the value of their data will have an advantage in today's uncertain market."
Individual comments from respondents illustrated the wide range of views on AI. Some supported it wholeheartedly. Others complained that, while beneficial, the CRE sector was "archaic." Others said it was hard to implement because of employee skill gaps. Yet others felt AI was dangerous and could lead to a dependence on inaccurate information.
There was broad agreement that humans must be in the loop and that AI should augment, not replace, roles. While 82% of respondents said AI tools are important for the future success of CRE, 17% said they don't plan to use them.
Respondents thought AI would be most useful for common area maintenance (CAM) reconciliation (51%), data trend spotting (47%), energy analysis (47%), financial outcome prediction (36%), anomaly detection (33%), automated responses to tenants (25%), facility management scheduling (15%) or other (5%).
However, the MRI Software found that AI preparation is slow and lacking. An "alarming" 54% of respondents said they had no AI-specific training available. Such as, it was mainly aimed at avoiding liability for AI outputs. The usual training did not focus on activities that improve the effectiveness of AI outputs.
"AI produces little value if it isn't used well," the analysis noted. "Especially with concerns about the privacy, security and trustworthiness of information going into and being produced by AI."
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