Nothing is Truly AI Proof

So Why Are Real Estate & PropTech Just Now Catching Up in the AI Race?

Every week, someone asks me a version of the same question: “What industries are AI proof?”

My answer always surprises people: “None of them are…anymore.”

Not construction. Not maintenance. Not architecture, design, or permitting. Not hardware.

Not even the slow grind of pulling permits and sitting through a Tuesday morning meeting at city hall.

We're already watching it happen in leasing, payments, fraud detection, and resident communications. The harder question is: What happens when AI comes for the labor side—the actual building, fixing, and upkeep of physical property?

We’ve all seen the meme that captures the moment perfectly: a billboard reading "Hey AI, try finishing this building."

We laugh because construction feels untouchable, but one VC recently told me: "95% of development will be automated by robots and AI within 10 years." This is obviously anecdotal and you may not agree with the exact number. But it's worth asking what's actually standing in the way of this AI automation, and for how long.

I see four key reasons real estate is moving a bit slower to adopt AI, and none of them are really about the technology.

Where the Resistance Comes From

1. If there’s no existential threat, there’s no urgency.

Most real estate assets retain their value and generate consistent cash flow. Because cap rates are typically higher than interest rates, owners tend to allocate the majority of their capital to the underlying asset, while investing only a relatively small amount in their technology stack.

This is the opposite of software companies, which often aren’t profitable early on and invest heavily in product development because software scales efficiently. As a result, they put far less capital into physical assets.

A building can't do that. It's stuck in one jurisdiction, bound by local zoning, taxes, and whatever the governing body decides. AI hasn't solved that problem…yet. But, what it has done is compress the research: Due diligence and data pulls that used to take months of travel now take minutes. It's just not the same as solving the immovability problem.

2. Trust runs on relationships, not dashboards.

Real estate isn't chasing home-run outcomes; it's more focused on steady, predictable returns. And predictable returns depend on consistency. This consistency has always come from human relationships: walking units, holding the keys, and building trust and a track record over time.

When a new system's data is wrong or incomplete, trust breaks fast. But once you're competing against operators who've already made the leap, standing still starts to carry a cost. I’ve seen this shift happen gradually at first, and then seemingly all at once, especially during market cycles.

3. "This is how it's always been done" is a hard habit to kill.

Every industry has lived through its horses-to-cars moment. It used to take weeks to build with hand tools, but now the same buildings go up taller and faster with machinery most crews take for granted.

The early version of any new technology usually looks like a step backward, and even early delivery drones were a punchline before they were useful. The resistance to asking "what if we changed this?" is what sticks with us.

The mistake many startups and AI companies make is assuming real estate wants disruption. In reality, most real estate operators value consistency above all else. When people live, work, and invest inside these assets, the goal isn't to disrupt operations, but to improve them without breaking what already works. Progress in real estate is often evolutionary, not revolutionary.

4. Regulation and integration protect the status quo.

New tech doesn't arrive without friction. Without System and Organization Controls (SOC) compliance, clean data management, or working integrations, operators can't take the leap—no matter how much time or NOI it could save them.

And plenty of owners genuinely don't feel the pressure yet. They're not selling, they're not struggling, so why change?

That may be true during upcycles, but the equation changes quickly when markets tighten. That's why we're seeing adoption accelerate faster than ever before.

Historically, those shifts have come after a change in management, new investors, or a market correction, not beforehand. And with the recent passage of the 21st Century ROAD to Housing Act, I believe investment in proptech and AI will further accelerate, pushing adoption across rental housing even faster.

Where is the Tide Turning?

Belief is starting to catch up to capability. When Tesla and Figure brought real robots into the field, the reaction was swift, even for those who said, “I’ll never believe it”.

Most people still need to see it to believe it, and there’s far more to see. But what once took two to five years is now happening in days and weeks.

That's the pattern I’ve seen with most disruption: it's slowly, slowly, then all at once. And the "all at once" part looks closer than it did a year ago, as these questions are increasingly finding their way into boardroom discussions among CEOs, CFOs, and institutional investors.

AI is already transforming everything from coding and camera-based analysis to error prevention and fraud detection. Its potential is particularly significant in construction, building development, and infrastructure retrofits, where the use cases continue to expand.

And if this means safer, better buildings and communities, then why wouldn’t everyone be on board?

What Does This Mean for Real Estate?

None of this suggests building crews are disappearing anytime soon. Instead, I see the real story is how capital, trust, entrenched practices, and regulation will influence which AI applications move quickly and which evolve more gradually.

If you want to understand what's coming next, pay close attention to these factors just as much as the technology itself. They will determine not only what is possible, but what becomes practical at scale.

So, what am I missing, and where do you see this heading? And will robots really be finishing buildings within a decade, or is that timeline a shot in the dark?