Blog
Operational notes on AI readiness
Patterns from inside transformation programmes. Not theory, not vendor talking points. What actually causes AI work to succeed or fail in real businesses.
-
Dirty data and AI: the cheapest mistake a small business can fix first
Most small businesses blame the AI model when the answers come back wrong. The real culprit is usually dirty data, and it is the cheapest readiness gap to fix first.
By Carl Chessum
-
AI without a tech team: what a small business can do first
Most small businesses think AI needs a tech team they do not have. Here is what an owner-operator can do first, before hiring or outsourcing.
By Carl Chessum
-
Your first AI use case: how a small team gets one project to pay off
Most small teams start five AI pilots and finish none. Here is how to choose one first AI use case, tie it to a number, and actually finish it.
By Carl Chessum
-
Seven signs your business isn't ready for AI
Most businesses overestimate how ready they are for AI. Seven signs your business isn't ready yet, across data, process, people, technology, strategy and governance.
By Carl Chessum
-
Why AI projects fail: the five patterns I've watched repeat for 25 years
95% of AI projects fail. After 25 years inside transformation programmes, the patterns are predictable. Here's what causes failure, and how to know if yours is at risk.
By Carl Chessum