Most AI consultants operate on a familiar model: scope a project, quote a fee, deliver the work, send an invoice, move on to the next client.
It works. But there’s a different play that I think is more interesting — and potentially a lot more valuable over time.
The idea: instead of charging for your time, take equity or a commission on results your automation actually generates. Build it once for one company. Then replicate it across every company in that industry with the same problem.
This is what I’ve been doing, quietly, for the past several months.
The Medical Building Deal
I’m working with a real estate company here in Austin that specializes in buying medical buildings. Their target sellers are doctors and dentists who own the building where they practice — dermatologists, primary care physicians, specialists — and who might want to sell.
Their lead generation process, when I first looked at it, was completely manual. A Philippines-based virtual assistant would go through public databases, identify building owners, paste names and contact information into a spreadsheet, and try to verify who actually owned what. Then a broker would work down the list, calling each one.
It worked. But it was slow, expensive to staff, and limited by how fast a human could click through databases.
I’m automating the entire pipeline with them. Automated research, owner identification, data enrichment, outreach sequencing — the kind of workflow that, once built, runs itself.
The deal structure: I’m not charging a project fee. In exchange for building and maintaining the system, I get 20% of whatever commission they earn on any deal that closes from leads the system generates.
The math on one transaction: a $10 million medical building, sold at a 2% broker commission, generates $200,000 in commission. My 20% cut is $40,000. From one closed deal.
Build it once. Every time a deal closes, the system generates a return.
Why Equity Beats Fees
The obvious attraction is upside. Project fees are capped — you scope the work, you get paid, you’re done. Equity positions grow with the business’s success.
But there’s something else. When you have equity in a company’s results, your incentives align with theirs in a way that straight consulting never does.
Mark Webster (co-founder of Authority Hacker) was telling me about a similar arrangement they have with a recruitment agency in South Africa they invested in. He said something that stuck with me: “When you’re just selling lead gen, there’s not really that much incentive to improve the conversion. But if you have equity, suddenly you care about all the other elements of the business. And there’s usually a lot of inefficiencies there too.”
When you have skin in the game, you notice things you’d otherwise let slide. You’re invested in the whole system working, not just the piece you built.
The Industry Replication Play
Here’s where it gets more interesting than a single deal.
Once you build a working automation for one company in an industry, you have something valuable: a proven template that solves a problem the entire industry has.
Medical office building brokers aren’t the only ones with manual lead gen pipelines. Every firm doing this kind of work — identifying building owners, sourcing off-market deals, doing outreach at scale — is running some version of the same process.
Once I can show that the automation works — real leads, real closed deals — I can take that template to every company in this vertical. Same equity structure. Same model.
Brad Jacobs wrote about this in How to Make a Few Billion Dollars. He’d identify industries stuck in outdated operational models — waste management, trucking, other fragmented sectors where nobody had bothered to modernize. He’d buy one company, build the technology, prove it worked, then acquire similar companies and roll out the same technology across all of them.
I’m not buying companies. But the underlying principle applies: go deep in one industry, build the automation once, then replicate it horizontally.
How to Think About Building This
Start with industries that are obviously manual. The best targets are businesses where a person is doing something repetitive that looks like data work — copying from databases to spreadsheets, verifying information by hand, sending similar messages to a list. If it involves judgment and relationship nuance, that’s harder. If it’s research and outreach at scale, that’s the sweet spot.
Look for high-stakes transactions. The equity model works best when individual deals are large. Real estate, healthcare contracts, professional services, commercial leasing — sectors where a single closed transaction generates enough commission that your 20% is meaningful.
The equity percentage should match your ongoing involvement. If you’re building and walking away, a smaller stake makes sense. If you’re maintaining and iterating over time, a larger ongoing percentage is appropriate.
Get the first one working before you think about scale. The replication play only works if the original automation actually delivers results.
Where This Fits
The AI consulting market right now has a lot of noise. Everyone is an automation expert. Project fees are getting competitive.
The equity model is different because it ties your compensation to outcomes, not deliverables. It also creates compounding value — a project fee is spent once and done. An equity stake in a working system keeps generating returns as long as the system runs.
Not every engagement should be equity-based. But for industries with high-value transactions, clear automation opportunities, and potential to replicate across multiple companies, this is the model I’m most excited about right now.
This approach is one of the core frameworks I cover in the 25X Productivity System — if you want to explore how to structure your AI work for maximum leverage, that’s a good place to start.
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