If you’ve ever tried to “bring AI into your business,” you know the temptation.
Not a 12-month transformation. One small, high-impact AI project in the next 30 days. Measure it. Share the results. Then stack the next one.
You see a viral LinkedIn/Instagram/TikTok post about a shiny new tool, think this is it, and… before you know it, you’re knee-deep in a $5K+ project that doesn’t actually move the needle.
The truth? Most companies use AI backwards.
They chase automation without first asking what’s actually slowing us down.
And that’s why they get stuck with:
Expensive bots doing irrelevant work
Automations built for problems that didn’t matter
Teams still drowning in manual tasks
We've run 100+ AI projects for companies from scrappy agencies to B2B giants - and the biggest wins never came from “more tools.”
They came from doing one thing first: a no-BS AI audit of the business.
Why Clarity Beats Tools Every Time
Hiring more people isn’t the only way to grow. Spot the invisible busywork, automate it, and redirect the time to revenue-generating activities - and you can scale without adding headcount.
The problem is, you can’t spot that busywork by guessing. You need to map it, measure it, and score its impact before you even touch an AI tool.
Start With the Bottlenecks
Every business has them - those processes that quietly burn hours and block progress.
Here’s what I look for:
The repetitive tasks nobody loves, but everyone tolerates
The steps that only work if a specific person is involved
Anything that requires copying and pasting between tools
“Export Button Theory” --> In short: Whenever users click “Export” in software, it often signals an unmet need - something proper SaaS software or AI automation can fully handle.
Talk to both leadership and frontline team members.
Leadership sees the strategy; the team feels the friction.
The gap between those two perspectives is where your biggest automation wins hide.
Pro tip: Feed both sets of answers into ChatGPT and ask it to spot contradictions.
Those are your goldmines.
Visualize Your Business like a Machine
Once you know where the friction lies, map your operations - not as an organizational chart, but as a flow.
Think in three engines:
Acquisition — how leads become customers
Delivery — how you fulfill and deliver
Support — how you resolve post-sale issues
As you map each step, tag:
Time sinks — highly manual, repetitive steps
Quality risks — prone to error or inconsistency
Every tag is a candidate for AI.
Score the Opportunities
Not all friction is worth fixing first. Plot each problem on two axes:
Business impact if automated
Current cost of running it manually
Top-right of that grid? That’s where you start - high impact, high cost. These are the processes where AI can free up hours and boost results.
Put a Number On It
AI isn’t just about “efficiency.” When you show exactly how many hours - and how much money - a process costs, it’s easy to get buy-in.
For each top opportunity:
Hours spent per week × hourly rate = annual cost
Half those hours reinvested in high-value work = annual revenue uplift
Add the two together — that’s your ROI potential.
Most companies are shocked when they see a single broken process bleeding five to six figures a year.
Why Most People Stop Here (and Why You Shouldn’t)
Mapping bottlenecks is the easy win.
The hard part - and the part that changes your business - is building and deploying the first automation.
Not a 12-month transformation.
One small, high-impact AI project in the next 30 days.
Measure it. Share the results. Then stack the next one.
