Updates on agency M&A trends and operational insights
After several conversations with agency founders recently, it's starting to feel like a fork in the road.
Here's the pattern: I'll be on a call evaluating an agency—good client roster, solid margins, strong founder. Then we get into how they actually deliver the work. And increasingly, the ones that worry me aren't the ones struggling with sales or positioning. They're the ones who've built their entire operation around manual processes and creative intuition alone.
That worked five years ago. It doesn't work now.
| The agencies I'm most excited about—the ones commanding premium valuations and winning better clients—have technical knowledge embedded in everything they do. Not a separate "tech team" bolted on. |
This isn't doom and gloom. It's a fundamental shift. And some agencies will fail because they can't disrupt their own manual processes while simultaneously serving clients. That's a real tension. I've lived it.
But here's what I know from being on both sides of agency M&A: the founders who figure this out aren't just surviving—they're building something significantly more valuable. The ones who don't are going to find themselves stuck with a business that's harder to sell, harder to scale, and harder to differentiate.
The technology has crossed a threshold. According to McKinsey's latest research on AI adoption, businesses using AI tools are seeing 3-15% revenue increases. Adoption isn't optional anymore. The only question is whether you're rebuilding the plane while flying it—or watching from the ground.
The problem: Most agency owners know they need to "do something with AI" but don't know where to start without blowing up their current workflows.
The approach: I use a three-layer audit borrowed from EOS and systems thinking:
Delivery layer – Where does human judgment actually matter vs. where are you just moving information around? Start automating the latter.
Operations layer – What's your project management stack? If your PMs are spending more time updating spreadsheets than managing client relationships, you've got a systems problem.
Knowledge layer – How does institutional knowledge flow? If it lives in people's heads or scattered Slack threads, AI tools can't help you—yet.
Start with one process in each layer. Small wins compound.
The outcome: You get a clear map of where technology adds leverage vs. where it creates noise.
I've been tracking a pattern across deal flow, industry content, and conversations with operators: the line between software company, service provider, and agency is dissolving.
Some are calling these "Software-Enabled Agencies" or SEANs. The model is simple: instead of charging for hours or seats, you charge for outcomes. You take accountability for the result, not just the deliverable.
This isn't theoretical. I'm seeing it in valuations. Agencies that can demonstrate outcome-based pricing and tech-enabled delivery are commanding multiples that look more like SaaS than traditional services.
| The market will reward whoever takes the most accountability for results. That means your pricing model, your delivery infrastructure, and your technical capability all need to align. |
The boundaries between software, services, freelancers, employees, and AI agents are blurring. The agencies that win will be the ones that stop thinking of themselves as "just" an agency.
I'm working through how to evaluate technical maturity during agency acquisitions—specifically, what signals indicate an agency can adapt vs. one that's too locked into legacy processes.
Ready to future-proof your agency? If you're actively rebuilding operations around AI or automation, I'd love to hear what's working (and what's not). Hit reply—I read everything.
|
Tristan Pelligrino
Partner
Aragon Holdings
|