The AI Value Map
A five-part series for mid-market leaders. A practical framework for finding, scoring, building, and deploying AI where it actually pays back — without the Fortune 500 budget or 12-month transformation.
- Part 1 of 5
The Mid-Market AI Playbook Is Missing
Lumen created $50 million in annual value with AI. Air Canada ended up in a tribunal. The difference wasn't the technology. It was the playbook. Here's the framework mid-market companies actually need.
Read the article → - Part 2 of 5
Your Employees Already Know Where AI Works. Start Listening.
82% of employees use unsanctioned AI at work. Most companies treat it as a security problem. It is — but it's also the best free market research a CEO will ever get, if you know how to separate signal from noise.
Read the article → - Part 3 of 5
A Scoring System for AI Projects That Actually Predicts Success
Klarna replaced 700 customer service agents with AI, then walked it back. The lesson isn't that AI failed — it's that the workflow was the wrong unit of analysis. Here's how to decompose work so AI handles what it does well, while humans stay on the parts that matter.
Read the article → - Part 4 of 5
Why Your AI Pilot Failed: A Three-Question Diagnosis
Most stalled AI initiatives aren't a model problem. They're missing one of three elements — clear instructions, the right context, or the ability to actually act. Three yes/no questions reveal which one in under an hour.
Read the article → - Part 5 of 5
The Simplest AI That Works Is the Best AI
Gartner predicts 40% of agentic AI projects will be canceled by 2027. The problem isn't AI — it's complexity mismatch. A four-tier ladder and the principle that prevents over-engineering: only graduate up when you've proven the lower tier doesn't work.
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