What Can't AI Do?

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95% of what marketers use agencies, strategists, and creative professionals for today will easily, nearly instantly and at almost no cost be handled by the AI... — Sam Altman, interviewed for AI First

Let’s be really honest: It’s a weird time to be a service business.

Even if we take Altman’s comments with a grain of salt, research (and our first-hand experience) shows that AI is becoming increasingly capable of knowledge work tasks — from writing content and generating creative to building custom strategies.

One recent study at Procter & Gamble found that individuals using AI performed just as well as two-person teams without it. AI, in effect, replicated the performance benefits of a human teammate.

“Individuals working with AI performed just as well as teams without AI ... one person with AI could match what previously required two-person collaboration.”

This trend has serious implications for service businesses:‍

• ‍‍‍Pricing: What happens to the billable hours model in a world of 10x (or 50x or 100x) efficiency?‍
• Talent: How will the roles of producers and individual contributors (writers, designers, developers, etc.) evolve? What new skills are needed?
• ‍Operations: How much can we scale with the same headcount? And how much are we willing to lean on the rented land of AI tools to increase productivity and output?

And, what we’ll look at today,

• Services: What will clients still need from us? With low-cost intelligence at their fingertips, what unique value do we offer them?  

The Competition Has Changed

Your competition is no longer just other firms. Your competition is your client, using AI in-house. Your competition is a team of two, doing the work of ten.

You cannot be faster or cheaper than AI. You have to be better.

And "better" = unique. Because when everyone has access to the same base information, the same base intelligence, what sets you apart is the experience only you have.

The Real Differentiator: The Stuff You Can’t Google (or “ChatGPT”)

As AI democratizes knowledge, it commodifies knowledge work. That means:

• Generic “expertise” becomes easier to replicate.
• “Consensus content” floods the market.
• Best practices become everyone’s practices.

What can’t be easily replicated?

Your lived experience, your judgment, and your intuition — all built over years of real work with real clients. That’s your proprietary data. And chances are, you're sitting on a gold mine.

It just might not look like one.

I don’t care if you’re an accounting firm, a SaaS company, a marketing agency, or a recruiter: You have lots of proprietary data.  

You don’t need databases, dashboards, or data lakes to have proprietary data. Instead, service businesses have:

• Case studies
• Tested and well-worn processes
• Insider knowledge
• Lessons learned (oftentimes the hard way)

So let’s talk about that: What this proprietary data is, why it can be hard to find, 4 places to look for it, and 3 ways to make the most of yours to win attention and business.

The DATA Framework: How to Identify and Use Your Expertise Moat

Expertise is more than just knowledge. It’s your differentiator.

I use a simple framework to help service businesses capture and scale their unique knowledge: just remember you’re looking for proprietary “DATA.”

D — Domain Expertise  

The deep insights gained from years in your field.

• What do true experts in your field know that others don’t?
• What do outsiders or novices consistently get wrong?
• How can you tell if a piece of content has been written by a true industry expert versus an outsider? (What are the “tells”?)

These are some of the clues to help you untangle the more surface-level details of your field from the deep well of knowledge that you possess.

A — Approach

The unique frameworks, processes, and heuristics you’ve developed.

• What proven patterns do you follow when tackling a new project? What steps do you take? Questions you seek to answer?
• What frameworks or methods do you follow instinctively?
• How do you diagnose and solve problems that stump others?

The answers to these questions will help clarify your unique approach to your work.

T — Talent

• What are you naturally great at?
• What do people consistently praise you for? What is it about the work or the experience that they remember? (T could also stand for “Testimonials.”)
• Why do clients or colleagues always come to you?

This is the secret recipe that you need to capture and scale.

A — Accomplishments

Your real-world, real-work experience.

• What have you done that an AI model hasn’t?
• What stories can only you tell?

Your past work is proof of your future value.

Use this framework to take stock of what your team really knows — the stuff you do so well, you forget it’s valuable. You might be surprised by what you uncover.

Why This Is So Hard (and So Valuable)

I’d bet that a lot of your best stuff is unstructured. It lives in Slack messages, onboarding calls, and muscle memory. It hasn’t been documented because until recently, it didn’t need to be.

But that’s changing.

The problem isn’t necessarily disorganization — It’s the broader ecosystem we’ve been working in.

For years, marketing rewarded sameness (or at least, similarness): listicles, best practices, top-of-funnel how-to’s.

The dominance of SEO and content marketing the past two decades taught us to prioritize what the crowd was already searching for — the high-volume keywords and the lowest common denominator. And so we built libraries of that 101 content: clear, digestible, easy to skim, and easy to scale.

But now, generative AI is here to do just that: Distill, summarize, and remix an internet’s worth of information.

But remember that LLMs are powered by statistical modeling of their training data. In short: AI does math, not meaning.

“A lot of people anthropomorphize these things because they ‘speak English.’ No, they don’t,” says Battle. “It doesn’t speak English. It does a lot of math.”

AI is flooding the market with knowledge. What it can’t replicate — and what service businesses must double down on — is lived experience, human judgment, and hard-earned wisdom.

To stand out from the statistical average of marketing, sales, and services, you need to find a way to bring together the the best of AI with the best of you:

1. Invest in Expertise, Not Just Automation

Use AI to scale what makes you great, not replace it.

2. Build Your (AI-Assisted) Playbooks

Create repeatable, AI-powered systems rooted in your experience and approach.

3. Focus on Differentiation Over Volume

Stop asking, "How can I do more?" Start asking, "What can only we do?"

What’s Next

In the coming weeks, we’ll dig into how to:

• Capture your team’s unspoken expertise
• Build searchable knowledge bases using tools like NotebookLM and Descript
• Train custom GPTs to replicate your approach
• Turn your first-hand experience into scalable products and processes

But for now, a first step:

Take 15 minutes to run through the DATA framework. What pearls of wisdom do you have, but take for granted? What are you overlooking that you could package, leverage, and scale?

Your moat isn’t simply what you know. It’s how you’ve lived it, used it, and made it work.

Let’s double down on that.