If You Can Document It, You Can Automate It 

The SOP-to-AI insight that changes everything 

There's a belief that's holding business leaders back from AI. It sounds reasonable. It feels true. And it's completely wrong. 

The belief is this: my work is too complex, too nuanced, too dependent on human judgment to be automated. 

Here's the reality: if you can write a standard operating procedure for it, you can turn it into AI. 

The Hidden Structure of "Complex" Work 

Think about the last complex decision you made at work. Maybe it was approving a discount for a strategic account. Or prioritizing which customer issues to escalate. Or deciding how to position a product for a specific market segment. 

It felt intuitive, right? Like you just "knew" the right answer. 

But if I asked you to explain your decision to a new hire, you could. You'd talk about the factors you weighed. The thresholds that mattered. The exceptions and edge cases. The context that shaped your thinking. 

That explanation? That's an SOP. And that SOP can become AI. 

What feels like intuition is actually expertise you haven't written down yet. 

The Documentation Exercise 

Pick a task your team does repeatedly. Something that takes real time and requires real judgment. Now imagine you're onboarding someone to do this task. What would you tell them? 

You'd start with the objective: "The goal is to..." 

Then the inputs: "You'll receive... and you'll need to look at..." 

Then the logic: "If X, then do Y. If Z, escalate to..." 

Then the output: "Deliver a... that includes... in this format..." 

Then the quality bar: "Good looks like... Watch out for..." 

Congratulations. You just wrote the instructions for an AI worker. 

From Services to Software 

This is the transformation happening across every industry: turning services into software. Turning human processes into automated ones. Turning SOPs into AI. 

It's not about replacing people. It's about codifying expertise so it can scale. 

The consultant who's diagnosed 500 similar problems? Their diagnostic framework can become AI that handles the first 80% of cases. 

The sales rep who knows exactly how to handle price objections? That playbook can become AI that coaches the entire team. 

The operations manager who can spot anomalies in reports instantly? Those pattern-recognition rules can become AI that monitors 24/7. 

The expertise doesn't disappear. It multiplies. 

What You Actually Need to Document 

Not everything. Just enough.

Start with: 

• The role: Who is this AI supposed to be? What's their job title, their expertise, their perspective? 
• The objective: What outcome are we trying to achieve? What does success look like? 
• The process: What are the steps? In what order? What decisions happen at each step? 
• The rules: What always happens? What never happens? What triggers exceptions? 
• The examples: What does good output look like? What does bad output look like? 

You don't need to capture every edge case on day one. Start with the 80% case. The edge cases will reveal themselves as you iterate. 

The Real Barrier Isn't Complexity 

The reason most AI projects fail isn't that the work is too complex. It's that no one took the time to document it clearly. 

We assume the AI should "just know" what we want. We give it vague instructions and blame the technology when it doesn't read our minds. 

But AI is like any new team member. It needs clear direction. It needs context. It needs to understand what good looks like. 

The investment isn't in technology. It's in clarity. 

Document your process. Write down your decision-making. Capture your frameworks. 

Your AI is ready to learn.  

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Start your journey to becoming an AI leader today by enrolling in our free AI fundamentals certification. 

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EverWorker 

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