What separates organizations that actually scale with AI from those stuck in demo mode. A practical guide for operations and business leaders — not engineers.
How to define, scope, and deploy an AI Worker for your first use case
The 4-layer architecture that makes AI Workers production-ready
Why pure agentic AI fails in operations — and what to do instead
How to build the org chart your AI Workers actually belong in
ROI framework: payback periods, cost structures, and make vs. buy
Real case studies: manufacturing, HVAC, legal — with actual results
3–6moTypical payback period
50%+Labor reduction in production
15yrOperational AI experience
Sterling North Partners
AI Workers: The Operational Playbook
~20 pages · PDF · Free
Get instant access
No fluff. No follow-up sequence. Just the guide.
What's Inside
01
The Capacity Problem Every Growing Company Has
Why headcount doesn't scale strategy — and why traditional automation hits a ceiling before you need it to.
02
What an AI Worker Actually Is
A precise definition. Not chatbots, not RPA, not pure agents. The 4-layer architecture explained plainly.
03
Deploying Your First AI Worker
How to identify the right bottleneck, scope the role, and go from concept to production without ripping anything out.
04
Governance, Accountability & the Org Chart
Where AI Workers sit in your organization. Reporting lines, KPIs, audit trails, and human-in-the-loop design.
05
The Financial Model
Make vs. buy. Cost structure. Payback period calculation. What to include in your ROI case to leadership.
06
Case Studies: Real Deployments
Logistics documentation, management reporting, and a whistleblower hotline — with actual outcomes.
07
The Agentification Trap
Why pure agentic AI underperforms in operations and how to use agentic reasoning without losing control.
08
Starting With Clarity
The first step isn't software selection. A framework for identifying the bottleneck worth solving first.
Written by
Philippe Marcotte
Managing Director & Founder, Sterling North Partners
15 years at the intersection of operations, AI, and execution. Led AI transformation work at McKinsey before it was mainstream, then built and operated automated production workflows as founder of a VC-backed network of tech-enabled medical clinics. As a partner at Cylad Consulting, he specialized in delivering AI-enabled solutions inside complex organizations. Sterling North is where all of that converges.
