---
title: AI Will Flatten Competitive Advantage | Founders Field Notes No. 04
description: When every brokerage has access to the same AI, access stops being an advantage. John Fischer on why judgment and strategy become the scarce resource.
image: https://www.pickup-studios.com/hubfs/field-notes-share-card.png
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[Founders Field Notes](https://www.pickup-studios.com/field-notes?hsLang=en)

No. 04

Volume I · September 2026Field Note

# AI Will Flatten Competitive Advantage

When capabilities become common, judgment becomes the scarce resource.

**John Fischer**, Founder, Pickup Studios[Download PDF](https://www.pickup-studios.com/hubfs/Pickup-Studios-Field-Notes-No-04.pdf?hsLang=en)

I recently found myself looking at two AI products that were supposed to do very different things. One was built specifically for a particular industry. The other was a general-purpose AI tool.

A year or two ago, the specialized product would have had an obvious advantage. It had been trained around a particular workflow, understood industry terminology and could perform tasks that a general-purpose tool couldn't easily replicate.

The gap wasn't nearly as obvious anymore.

That's been happening a lot lately.

Capabilities that seemed remarkable six months ago show up somewhere else a few months later. Features that companies once built entire products around become part of larger platforms. Things that required specialized technical knowledge become accessible through a prompt and a credit card.

It has made me wonder whether we're entering a period in which technology creates competitive advantage and erases it at almost the same time.

§

## We've seen a version of this before.

For a long time, technology itself could differentiate a real estate company.

A brokerage with a great website had an advantage over one with a bad website. Then everybody got a decent website.

Mobile search was a differentiator. Then it became expected.

CRMs, automated marketing, digital transaction management and electronic signatures all followed some version of the same path. Early adopters received a period of advantage before the capability became widely available.

AI is moving through that cycle much faster.

If one brokerage finds a useful way to automate listing marketing today, its competitors won't need three years to catch up. They may need three months. In some cases, three weeks.

And they don't necessarily have to build anything themselves. The underlying capabilities are spreading too quickly.

§

## This creates a problem with the way companies talk about innovation.

There's a tendency to point to technology as evidence that an organization is innovative.

We have an AI assistant.  
We've automated our marketing.  
We're using AI for recruiting.  
We've built a custom agent tool.

Those things may be useful. I'm just not convinced they'll remain differentiators for very long.

If the same underlying models are available to everyone, the same software vendors sell to everyone, and competitors can reproduce useful features relatively quickly, access to technology becomes less interesting.

> What you do with it becomes more interesting.

That sounds obvious, but it has fairly significant implications for how companies invest.

§

## The scarce resource may be judgment.

Most brokerage leaders I've met don't suffer from a shortage of ideas. Their problem is deciding which ones deserve attention.

There are more technologies to evaluate than they can reasonably test, more data than they can meaningfully use, and more opportunities to automate than they can responsibly pursue at once.

AI is going to increase all three.

So perhaps the important organizational capability isn't being first to discover new technology. Maybe it's developing a better filter.

Which problems are worth solving?  
Which parts of our business should remain human?  
Where would speed actually improve the experience?  
Which capabilities should we build ourselves, and which are likely to become commodities we can simply buy?  
What are we doing today that we should stop doing entirely rather than automate?

Those are judgment calls. AI can certainly help inform them, but it can't make them independently of what a company is trying to become.

§

## Strategy gets more important when capabilities become common.

Imagine two brokerages with access to essentially the same technology. They can generate similar marketing materials. They have comparable automation. Both can analyze their data, build AI assistants and give agents sophisticated tools.

One of them still has to make better decisions.

Maybe it understands its market more deeply. Maybe it has a clearer point of view about the type of agents it wants to attract. Maybe its leadership is better at eliminating unnecessary work. Maybe it has developed an unusually good training culture. Maybe it knows exactly where technology improves the customer experience and where a human being should pick up the phone.

None of those advantages comes from having access to AI. In fact, AI may make them more visible.

> When everyone has similar tools, differences in judgment, culture, execution and strategy become harder to hide.

§

## I'm skeptical of large technology bets made primarily for differentiation.

There are certainly situations where proprietary technology makes sense. Some organizations have unique data, workflows, scale or business models that justify building something themselves.

But "our competitors don't have this yet" is becoming a dangerous reason to spend a lot of money. They may have it sooner than you think.

Before building something proprietary, I would want to understand whether the real advantage is the technology itself or something underneath it: proprietary data, a unique process, distribution, customer relationships, specialized knowledge, or the ability to execute better than competitors.

> Those things are harder to copy.  
> The feature usually isn't.

§

## There is some good news in this.

Smaller companies have spent years competing against organizations with technology budgets they couldn't touch. AI narrows some of that gap.

A smaller brokerage can now accomplish things that once required a marketing department, a data team or expensive custom development. A good operator with a handful of modern tools can create an impressive amount of leverage.

That doesn't mean scale stops mattering. Large organizations still have capital, data, distribution and other advantages that small companies don't. But access to sophisticated capabilities is becoming much more democratic.

For independent brokerages in particular, I think that's worth paying attention to.

The question is whether they'll use that access to imitate larger competitors or to become more distinctly themselves. I'd choose the latter.

§

## We've spent a lot of time asking what AI can do.

That was probably necessary at first. We needed to understand the technology.

I'm increasingly interested in what happens after everybody knows what it can do.

If powerful AI becomes ordinary — embedded in the software we already use and available to nearly every company in the industry — then simply having it won't say very much about a business.

> We'll have to find other ways to be good.

A clear strategy. Better judgment. Genuine expertise. Strong relationships. Useful proprietary knowledge. An organization capable of making decisions and acting on them.

None of those ideas is particularly new.

That's partly why I believe they'll matter.

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