

In New York City’s commercial real estate world, few names carry as much weight as Bob Knakal. Having personally brokered the sale of over 2,300 buildings valued at more than $22 billi...


On Friday nights in the 1990s, millions of Americans would drive across town, stand in line at Blockbuster, and hope the movie they wanted was still on the shelf. If it wasn’t, they settled for something else. And if they returned it late? They paid a fee they resented but never questioned.
That was just how it worked.
Until it wasn’t.
It is a pattern Ben Handelman, Director of Automation and Operational Intelligence at Keasy, knows well, and one he believes is about to repeat itself in property management.
What Netflix understood, and what Blockbuster missed, wasn’t about movies. It was about incentive alignment. Blockbuster made more money when the customer experience got worse. Late returns, long lines, scarce inventory: these weren’t bugs in the business model. They were features. Netflix flipped that entirely. For the first time, a media company made more money when customers were happier. Same content, same audience, radically different architecture.
You could tell the same story about taxis and Uber. In major cities, taxi companies controlled access through medallions, restricted supply to keep prices high, and dispatched drivers through human operators. Drivers were paid by meter time and route length, meaning longer trips and slower routes were good for revenue. Passengers optimized for getting somewhere quickly. Drivers were paid when it took longer. Uber did not buy medallions or hire drivers. It built a marketplace that connected supply to demand dynamically, and for the first time made more money when trips were faster, routes were cleaner, and idle time was lower. Same roads, same riders, radically different incentives.
Or travel agents and Expedia. The pattern Handelman identifies is almost eerie in its consistency: a highly fragmented, headcount-driven industry with a conflict of interest baked into its revenue model, followed by an outsider who re-aligns incentives through technology, and then a collapse that, in retrospect, looks inevitable.
Property management, he argues, is next.
The structure is almost identical. Leasing, maintenance, renewals, compliance, vendor dispatch: most of it still happens locally and manually. Companies grow by hiring more coordinators, more leasing agents, more maintenance staff. And while many have layered in software and automation, the underlying model is largely unchanged. Technology helps a human make a decision, but the human still makes it.
The conflict of interest runs deep. Maintenance markups, turnover fees, after-hours premiums: the more friction in the system, the more revenue it generates. Owners want occupancy, stability, and controlled costs. The incentive structure often rewards the opposite.
What is different now, Handelman believes, is that the tools to re-architect this model actually exist. Not just to digitize the old workflows, but to move decision-making itself into systems rather than people. When the same situation happens twice, it should not require fresh judgment the second time. The system should recognize it, apply known rules, and route only the genuinely novel cases to human review.
This is what Handelman means when he talks about “full-stack AI”: not replacing people, but being intentional about where judgment lives. People remain essential for empathy, authority, and compliance. But when decision quality lives in the system rather than in any individual, something important changes. Outcomes stay consistent even as teams evolve, and efficiency compounds rather than simply scales.
The companies that win the next wave of property management, in his view, won’t be the ones with the most staff or the most sophisticated dashboards. They’ll be the ones that figured out how to make the business model work with the landlord’s interests, not against them, and built systems disciplined enough to stay that way as they grow.
Buildings aren’t going away. Residents aren’t going away. But highly fragmented, headcount-scaled, friction-monetized coordination layers have a poor historical track record once aligned incentives and technology-enabled scale enter a market.
History doesn’t repeat. But it does rhyme.
Ben Handelman is Director of Automation and Operational Intelligence at Keasy, a property management company built on flat-fee pricing, AI-driven workflows, and landlord control.
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