The Founder’s AI Advantage: Building $100M Companies in the Intelligence Era

Hey friends. Hope you had an amazing week.  I love our ability to have creative outlets, like this, to share, learn, and network.

About a month ago, I joined the Post Exit Founder (PEF) group and had the chance this week to attend my first in-person meetup.  To qualify, you have to have financially exited a company that you (co)founded and are no longer part of the day-to-day.  There are about 4,000 members worldwide and the group is AWESOME…    

I’ve spent the recent chapter of my journey talking about AI, Automation, Tech.  The main reason is that I see a major shift in how we do business coming.

But, this newsletter is about Venture Building: Tech | Talent.   We can’t forget that people do business with people.  The human element of creativity, ideas, and relationships aren’t going away anytime soon.

But the tools have changed.          

I want to talk this week about the power of AI, Automation, and Technology inside your business.  We’re using them, helping others implement them, and building businesses with them.  

You can too… Let’s dive in.

The Underrated AI Advantage for Scaling Founders

I keep coming back to this question:

How are founders at growth-stage companies, those in the $5M to $100M zone, using AI differently than the big corps and/or the brand-new startups?

Here’s the thing:

Most AI chatter out there is stuck at the enterprise or seed-stage level.

But the companies best positioned to really capitalize on AI? They’re right in the middle: scaling, scrappy, and ready to punch above their weight. If you’re at the helm of one of these businesses, the opportunity is massive.

The Scaling Advantage: $5M–$100M Sweet Spot

Let’s break it down. Why are scaling companies in this bracket uniquely poised for AI-fueled growth?

• Speed and Agility: You don’t have corporate red tape. No “14 meetings to make a decision.” You can move.
• You Own Your Data: You’re not drowning under technical debt or lost in an ocean of messy, decades-old systems—and with a few years under your belt, you actually have enough data to work with.
• Founder Energy: Decision-making is still founder-led. You can bet the business, redirect strategy, or jump into new territory fast—no committee, no quarterly call hand-wringing.
• Growth Mindset (Real, Not Just on a Slide): You’re still hungry. You care about scaling, not just squeezing out 1% efficiency.
• Magnet for Talent: For AI engineers, you’re not too big and bureaucratic, but you’re not a moonshot seed-stage risk, either.

Want some Use Cases?

Here are a handful of USE CASES we’ve worked through recently with clients.

Rethinking AI: Beyond Efficiency, Toward Growth & New Categories

Too many folks still think AI is about automating back-office busy work. That’s one way, but most of that is just some simple automation.

The top founders I talk with are using AI for three things:

1. Creating New Categories

The most ambitious founders use AI to create whole new categories.  Products or services that weren’t viable before.

• Think: shifting from “business intelligence software” to “predictive business guidance.” One founder told me this single repositioning, enabled by AI, doubled their valuation multiple before exit.

This is your time to dream…  and dream BIG cause I bet it’s possible. 

2. Reinventing Business Models

AI enables you to repackage, reprice, and rethink what your company offers.

• Moving services to products (AI-powered expertise as a repeatable solution? Gamechanger.)
• Switching from one-off sales to recurring AI-driven “guaranteed outcomes” (think: predictive maintenance, uptime as a service)
• Harnessing network effects:  each new customer improves your system, compounding your edge.

3. Building Unfair Data Advantages

The real long-term value? “Data moats.”

Not just collecting data, but turning it into unique, defensible AI capabilities that others can’t easily replicate. One founder described it as a “virtuous cycle”: 

customers bring data → AI gets better → product improves → more customers come → moat gets even wider.

Pause for a second:

What unique data flows through your business every day? How could you use that to create new value, new categories, or even a new business model?        

The Founder’s AI Playbook: How to Actually Get This Done

Drawing from 20+ years in entrepreneurship, launching multiple ventures, working with hundreds of founders, and exiting a few businesses, here’s a 3-stage roadmap:

Stage 1: Strategic Positioning ($5M–$15M)

• Identify your potential data moat: What unique info do you have now, or could you collect?
• Pick one high-leverage AI focus point: Don’t spread yourself thin. Nail a core workflow where AI moves the needle for real customers.
• Map your talent strategy: Hire? Partner? Acqui-hire? Don’t try to build every skill in-house if you don’t need to.

Pro Tip and Reminder to Myself: Focus your AI efforts on a specific workflow where you hold a data edge, instead of chasing every shiny “AI for X” idea.

Stage 2: Execution + Validation ($15M–$40M)

• Show value and killer UX: Launch your first customer-facing AI capability and obsess over clear, measurable impact.  Plus, make the user interface awesome.
• Double down on data infrastructure: Structure, clean, and enhance your data so it compounds value over time.
• Craft your AI narrative: Don’t just talk “AI.” Tell success stories and document real outcomes achieved.

Pro Tip and Reminder to Myself: Organize your data and tell a compelling story. 

Stage 3: Acceleration + Moat Building ($40M–$100M)

• Scale winning AI innovations across new use cases.
• Systemize AI workflows: Make improvement, deployment, and measurable outcomes repeatable.
• Fortify your moat: Plug holes in your data with partnerships, integrations, or strategic acquisitions if needed.
• Prepare for scrutiny: Document your AI edge and ensure systems can withstand due diligence.

Exit, Premiums, and The Truth About Valuation

If you’re building with a potential exit in mind, know this: AI is a multiplier, but only if it creates real, defensible value.

Here’s what I’m hearing (and seeing):

Valuation Premiums:

• Proprietary data + AI: 3 to 4x premium
• Unique AI in traditional markets: 2 to 3x
• Efficiency-only internal AI: maybe 1X

Acquirer Motivation:

• Compress their AI timeline
• Access to proprietary data
• Talent acquisition
• Defensive (block competitors)
• Unlock new markets

The opportunity here is for established businesses whose founder is ready to exit and the business can’t operate without them…  

Final Thought: The Founder’s Inflection Point

We’re at a transition period in tech that we’ve never seen before.

The AI knowledge gap is only widening.  As a scaling founder, you have a window where resources, speed, and ambition align. This is rare air.

The question for all of us:

Will you define how AI changes your category or will you be forced to play catch up as someone else rewrites the rules?

I know which side I want to be on.

Until next time, keep building with purpose, people, and process!

Andy

P.S. If you’re scaling a $5M to $100M business and want to talk about anything related to launching, building, scaling, or exiting your business, let’s connect. 👇