The commercial real estate industry spent years chasing smart buildings. Smart locks, smart thermostats, smart access control. The pitch was simple: connect your systems and they’ll take care of themselves. According to Bill Douglas, CEO of OpticWise, that framing has always been wrong, and the gap between what smart buildings promised and what they actually deliver is why so many owners are still making decisions without the data they need.
“Smart is a misnomer,” Douglas says plainly. “It’s not actually smart. Only as smart as we program it to be. Computers aren’t smart. They’re just really fast at making decisions.”
What “Smart” Actually Means
A smart lock, Douglas explains, does not think. It checks two conditions: do I recognize this person, and are they authorized to enter? Every apparent decision is just a binary check inside an if-then loop. There is no intelligence, only speed.
The problem is that the label sets up the wrong expectations. When an owner installs a smart system and finds that it does not integrate with the other systems in the building, does not share data, and cannot be queried for root cause information, they assume the technology fell short. In Douglas’s view, the concept fell short long before the technology did.
“Smart came out with PropTech pre-pandemic and became really popular,” he says. “A smart lock system is one part of access controls. Does it integrate with outside locks? Does it integrate with parking? With the pool and the gym? That still doesn’t make it smart. It just makes it comprehensive.”
Autonomous Is a Different Category Entirely
The shift Douglas advocates is from smart to autonomous. The distinction is meaningful. A smart system reacts to inputs. An autonomous property acts on real-time data, executes decisions without manual intervention, and adapts to whatever the owner has defined as the current priority.
“Autonomy is a decision-making engine,” Douglas says. “That we and our clients build together. It deploys all those decisions based on real-time data, emphasized real-time. If I’m trying to make a utilities or occupancy decision and the data is two weeks old, it’s useless.”
The key difference is ownership of the strategy. In an autonomous model, the owner defines what the property should optimize for. It might be utility reduction at one asset, occupancy improvement at another, and CapEx protection at a third. The system executes. The owner adjusts the strategy when priorities change.
The Property Brain and Portfolio Brain
Douglas uses two terms to describe how this plays out in practice. A property brain is a unified data environment built on a single building’s operating technology data. A portfolio brain aggregates data across multiple properties, giving ownership groups the ability to compare performance, benchmark across assets, and identify where intervention is needed.
This is the architecture that enables the benchmarking question most asset managers cannot currently answer: why does one comparable property cost more to operate than another? Without a property brain, the data lives in separate vendor systems and cannot be compared. With one, that question becomes answerable in minutes. The Peak Property Performance podcast explores this model in depth with real operators.
How Long Does the Transition Take?
Douglas is direct that there is no single answer, but he is equally direct that faster is not always better.
“You can go as fast as you want, with the limitation that you must have at least six months of data,” he says. “We’re strong advocates for crawl, walk, run. We’re not trying to come in and flip a switch and make everything work overnight, because that is impossible.”
The crawl phase means starting with one system, one that is low-risk and likely to show early results. The walk phase means expanding to a more significant system and learning from what broke during the crawl. The run phase is full deployment across the property, with a human in the loop reviewing outputs until the process becomes routine enough to step back.
“Once the human’s bored, put them somewhere else and make it fully autonomous,” Douglas says. “But they’re going to find things that AI assumed. You didn’t give it the if-then loop. You didn’t tell it what to do if this happens. So it jumped to a conclusion.”
The discipline to go slow is part of what Douglas believes separates owners who successfully make the transition from those who implement too fast, encounter resistance, and retreat to the status quo.
For owners tired of being told their building is smart when it still cannot tell them why their utility costs are up, the distinction Douglas draws is worth taking seriously.
About OpticWise: OpticWise is a digital infrastructure and data strategy firm focused on commercial real estate. The company helps owners and operators move beyond point solutions toward autonomous building operations, with a foundation built on owned data and vendor-agnostic infrastructure. Learn more at opticwise.com.
Disclaimer: This article is based on information provided by the expert source cited above. It is intended for general informational purposes only and does not constitute legal, financial, or real estate advice. Readers should conduct their own research and consult qualified professionals before making any real estate or financial decisions.