Commercial real estate has always been
an industry built on information, but for decades that information moved
slowly. Documents passed through inboxes, analysts transferred numbers into
spreadsheets, underwriting teams created static models, and asset managers
worked from reports that often reflected conditions weeks or months after they
had already changed. According to David Bratslavsky, that operating model is
approaching a breaking point. After spending years inside commercial real
estate workflows and observing how firms process deals, evaluate opportunities,
and manage portfolios, he believes artificial intelligence will not simply
improve existing systems—it will fundamentally change how the industry works.
David Bratslavsky view is not centered
around dramatic predictions about machines replacing professionals. Instead, he
sees the future being built through something less glamorous but far more
important: eliminating friction in how data moves across organizations.
Commercial real estate still depends heavily on documents such as rent rolls,
leases, T12 statements, offering memorandums, and comparable reports. Even in
sophisticated firms, extracting and organizing information often consumes
enormous amounts of time. The result is slower decision-making and operational
bottlenecks that become increasingly expensive in competitive markets.
From David Bratslavsky perspective, this
is the first problem artificial intelligence solves at scale. As data
extraction and normalization become increasingly automated, firms gain access
to structured information almost instantly. What once required hours of manual
work begins happening in minutes. While that may sound like a simple efficiency
improvement, he argues it creates much larger downstream effects because every
decision built on top of that data accelerates as well.
The bigger transformation begins once
data becomes continuous rather than static. Traditional underwriting captures a
moment in timea snapshot created before acquisition and often revisited only
periodically afterward. David Bratslavsky believes future underwriting will
operate more like a living system. Financial assumptions will evolve as new
information enters the business. Market comparables will update regularly.
Property performance will continuously influence projections. Instead of
creating models and filing them away, firms will maintain active investment
intelligence that changes alongside operations.
This shift eventually reaches asset
management. Historically, asset managers spent significant energy collecting
updates and assembling reports before making decisions. In an AI-enabled
environment, those workflows begin changing. Systems identify unusual operating
patterns, surface lease opportunities, prioritize capital projects, and provide
recommendations before issues appear in financial outcomes. Human teams remain
responsible for judgment and execution, but their role becomes more strategic
because less time is spent gathering information.
David Bratslavsky believes this
progression ultimately leads toward an environment where software coordinates
increasingly complex workflows across sourcing, diligence, reporting, and
operations. Professionals still define objectives and make final calls, but
intelligent systems handle orchestration across connected processes.
For firms operating in commercial real
estate today, the takeaway is straightforward. The winners are unlikely to be
those attempting to replace existing operations overnight. Success will come
from integrating AI into real workflows, improving how decisions are made, and
building systems that adapt faster than competitors. According to Bratslavsky,
the future of CRE is already beginning—and firms that move early will shape
what comes next.
Comments
Post a Comment