Most leaders treat AI implementation like a single coat of paint, they try to cover everything and end up with a streaky, incomplete organization.
The goal isn't automating every interaction. It’s knowing exactly where a human touch is valuable and where it’s actually a bottleneck.
If you are still using AEs to answer "How much does the Pro tier cost?", you aren't building a relationship...you’re adding latency to a 90 second answer.
AI implementation is not a tooling decision. It’s a labor allocation decision.
Two Questions You Need to Answer
Every customer interaction comes down to two questions
Is it simple or hard?
Does it need a human, or not?
Put the work into one of four boxes.
1. Simple + Low Human Need
Examples: Pricing questions, Password resets, Booking a demo, “Do you integrate with X?”.
The Play: Automate it.
If someone is waiting on a person for this, your system is broken. Response time is revenue.
2. Simple + High Human Need
Examples: Renewal check-ins, Usage follow-ups, Late invoice reminders.
The Play: AI drafts it. A human reviews and sends.
The message stays personal. Time spent goes down.
3. Hard + Low Human Need
Examples: Long RFPs, Security questionnaires, Contract edits.
The Play: AI does the first pass. A human signs off.
Don’t spend judgment on formatting and copy-paste work.
4. Hard + High Human Need
Examples: Big negotiations, Strategic renewals, Fixing a broken account.
The Play: Human-led.
This is where responsibility lives. Buyers don’t want a response. They want someone accountable.
AI shouldn’t replace everything. Start with the simple stuff. If simple work is sitting on a person’s calendar, your system is wrong.
Automate the information. Free up your people for the hard, high-trust work. AI handles information. Humans handle responsibility.
This is how we design Autonomous Teams. The full breakdown is here.
That’s it for today. Connect with me on Linkedin if you actually want to understand what an Autonomous Organization looks like in the real world.
