"AI can automate your business."
"AI will 10x your productivity."
"There's this new tool you can just plug in, works out of the box."
Yeah... You've probably heard it all before.
Newsflash: most of the time, it doesn't work.
Not because the AI or the tech is broken... but because the business wasn't ready for it.
If you've ever watched a customer support ticket bounce between three different agents… or had a customer rage-quit after explaining their problem for the third time - this is why:
Your tickets aren't getting to the right people.
27% of support tickets land on the wrong desk. That means 1 in 4 customers gets transferred, re-explains their problem, and waits longer for help.
Misrouted tickets slow down support, kill customer trust, burn team time, and spike churn. Trying to patch it with a chatbot only makes it worse.
So instead of building another chatbot, I built them a system to fix the root cause. And the misroutes were cut by 89% in a couple of weeks.
90% of AI customer support implementations crash and burn within 3 months.
Not because the technology doesn't work. It's because everyone starts with the same mistake: they start with a chatbot.
While your competitors are burning cash on chatbots that make customers angrier, I'm going to show you the 6-step system that actually works. The same system that took one team from 27% misrouted tickets to under 3% in just a couple of weeks.
The companies getting the biggest AI returns aren't the ones with the most AI projects.
They're the ones with the fewest.
While everyone else is trying to "AI-transform" their entire business, smart companies are using the 80/20 rule to identify the single process that's causing 80% of their operational pain, and solving just that one problem first.
The result? They're seeing 10x better ROI because they're going deep instead of wide.
Only 1 in 5 AI projects make it to production.
You've seen the pitch deck.
AI will automate your operations, cut costs by 40%, give you superhuman insights, and transform your business overnight.
So you hire consultants, build a proof of concept, and the demo works perfectly.
Then you try to deploy it in production. Everything breaks.
80% of AI projects fail after proof of concept.
Smart leadership, decent budget, good intentions; but they still burned through 6 figures on AI and got nothing.
This wasn't some startup making rookie mistakes. This was a successful company with experienced engineers and proper funding. They followed all the "best practices," hired a big-name consulting firm, spent months on research and planning, and built impressive prototypes.
Sound familiar?