Welcome to this introduction to our five part guide on Applying AI at your organization.

Here's a sobering statistic: Over 70% of manufacturing plants have adopted predictive analytics, yet only a fraction see meaningful gains. The winners show 2-3% higher productivity - nearly a million dollars in increased sales for the average plant. 

The losers? They've got expensive AI systems gathering digital dust.

The difference isn't in the AI - it's in how they applied it.

I've spent years studying how companies succeed and fail at AI and process improvement. 

If you’re the type that wants the tldr – here it is. If your job is to apply AI, your first job is to make the process, organizational structure, and compensation incentives ready for it. Applying AI is another word for change management, you’re hiring a new role and need to place them where they can have an impact.

The pattern is clear: The winners don't start with AI at all. 

They start with their processes. They understand that AI isn't magic - it’s a tool. And like any tool, it works best on well-defined problems with well-understood constraints within a system where actors have the right incentives.

This guide will spare you a lot of pain so you can be one of the winners. No buzzwords. Just a practical roadmap for turning AI from a boardroom buzzword into bottom-line results.

• The First Step to AI Success: Getting Your Process House in Order 
• Process Optimization: Why Most AI Projects Are Doomed Before They Start
• AI Implementation Strategy: Moving from Process to Production (Without Losing Your Mind)
• Testing & Iteration: Where AI Dreams Meet Reality
• Scaling & Expansion: The Hidden Physics of AI Success

Read in whatever order you’d like. Please share this guide or, if you want to tell me I’m full of anything, ping us at hello [a†] v1.co.

‍

Sit-Back and listen to a Podcast Version of This Series

‍

Enjoy!