I’ve been thinking a lot about AI lately - what it’s great at, and what it’s not great at. I'm tempted to say "what it's not great at (yet)" but it's unclear to me whether or not the "last-mile" will ever be perfected enough for CRE brokers to truly lean on it without fact-checking.

Right now, AI is enormously powerful…just not for everything, all at once.

Where it shines is in pieces, embedded inside real workflows and CRMs, doing specific, high-leverage work that humans no longer need to spend hours on.

This is where real productivity gains exist at the moment. Given that Enaia primarily supports Occupier and Landlord reps, we've built AI into our application in several critical ways.

For example, in Enaia:

• Users can scour companies and identify who the actual decision maker is through AI detecting who most likely decision makers are based on title, company size, industry and more. As a former broker, I was trained to think "CEO, COO, CFO, etc." are the only titles to look for but we've heard users say "I didn't even realize the company had a "Head of Workplace" or "Global Real Estate Director" until Enaia suggested this.
• Users can then surface email addresses and phone numbers, not only replacing the need for third-party applications but, most importantly, saving the back-and-forth between browser tabs and thus reducing cognitive load (a big deal with software applications).
• Ultimately, we're saving brokers hours of manual research and guessing while simultaneously centralizing their workflows and making them more competitive.

Another exciting example is that Enaia users can run complex financial lease analyses in seconds (yes, seconds).

Here's a video of Enaia's AI lease financial analysis:

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• Drop in a leasing proposal
• Have AI run the full financial analysis from either the Occupier's POV (focused on Total Occupancy Costs) or the Landlord's POV (focused on Net Effective Rent
• Review results, tweak if needed and then generate a client-ready deliverable

But this goes further than just “analyze and summarize.” This is where robust, purpose-built AI agents come into play.

An AI agent can also propose forward-looking strategy:

• What a smart counteroffer should look like to optimize for better economics, shorter term, etc.
• What happens if the tenant adds lease term?  How will a landlord or Occupier see this?
• How to reduce occupancy cost while maintaining rental integrity based on the profile of the Landlord or Occupier
• How different structures affect NER, cash flow, and risk

In other words, it helps brokers pressure-test and sensitize scenarios instantly and walk into negotiations better prepared.

That’s hours, sometimes days, of work collapsed into minutes.

But here’s the key part that often gets missed: humans stay in control.

• AI should draft.
• AI should analyze.
• AI should propose.

Humans approve, override, adjust, and apply judgment.

That combination of machine speed plus human involvement, is where the real value is. I'd argue it's also the future of AI which is why I'm optimistic.

This matters a lot for the CRE industry.

Brokerage has historically been an apprenticeship business. You learned by sitting near great brokers, watching deals unfold, and slowly building pattern recognition over years.

AI stands to change that. What took years to become an expert may no longer been the case going forward.

AI doesn’t replace experience, but it compresses the learning curve. It democratizes access to high-quality analysis and decision support. It trains best practices and expedites the growth stage of a broker's career.

So the edge shifts.

The future top brokers won’t just be the ones who lean on their transaction history.

They’ll be the ones who:

• Better identify opportunities and cut straight to relationship building
• Convey value clearly, with time-to-value being a clear value proposition
• Establish trust through data and technology leverage
• Harness technology to do 10x more with the same amount of time

There’s another implication that people don’t always like to talk about:

As AI absorbs more of the analytical and administrative workload, brokerages may simply need fewer layers of support.

Financial analysts, admins, research teams, external consultants. Historically, these have been supporting cast-members for sales leaders (brokers and others who sell across the organization).

These support-roles will still exist, but they will no longer be required at the same scale for every deal.

The brokers at the tip of the spear - the ones originating, advising, negotiating, and managing relationships, stand to benefit the most. No replacement of brokers. No magic buttons.

Today's top producers will be more powerful and capable of scaling bigger, better teams. From the company's perspective, margins increase and brokers will likely seek to participate in overall margin expansion.

From my vantage point, that’s how AI actually changes work:

Incrementally.
Inside real tools (not endless AI hacks that are self-constructed and disconnected).
Solving real pain.

And honestly, that’s far more interesting than any sci-fi version of it.

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