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Opportunity Selection: Which Workflows, Which Shape

Two axes, one bias to correct, and a shape ladder — replacing 'AI brainstorming' with an actual method.

AI Strategy & Implementation · Expert · 10 min read · 4 quiz questions

By Ronan Liedmeier, fractional head of growth and course author · Reviewed 13 October 2026

What you will learn

  • The two axes that predict survival
  • The bias to correct: front-office glamour, back-office ROI
  • The shape ladder (Anthropic)

Lesson preview

Good opportunity selection runs three filters in sequence. First: does this workflow have real friction and a closable learning loop — a place where AI output can be checked and corrections fed back in? Second: can the solution be made domain-specific (built around the vocabulary and rules of one narrow function) AND deeply integrated (living inside the process, not beside it as a chat window)? Third: what is the simplest technical shape that serves this workflow — a single model call, a composed pipeline, or a full agent? A candidate that passes all three filters is rare. That's the point. The 5% of AI projects that survive weren't lucky; they were selective. Replotting the GenAI Divide data reveals a clean pattern. Projects survive the pilot-to-production cliff based on two variables: Domain specificity — does the system actually embed the vocabulary, rules, and edge cases of one narrow business function? Or is it a generic model that happens to be pointed at a new problem? Workflow integration — does the system live inside the process, with memory and context, so it shapes decisions in real time? Or does it sit beside the process as a chat window people open when curious? Low on both axes is where the 95% of failing projects live — generic chatbots dropped into processes they don't touch. High on both — deeply integrated, domain-specific, most often delivered by a specialized vendor — is where success rates roughly double.

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Frequently asked questions

Who is "Opportunity Selection: Which Workflows, Which Shape" for?
This Expert module in AI Strategy & Implementation is for operators, founders and growth teams who run AI in real work and want production-grade judgement. It takes about 10 minutes and ends with a 4-question quiz.
Do I need to code?
No. This module is about decisions, economics and implementation planning, so no coding is involved.
What comes before and after this module?
Before "Opportunity Selection: Which Workflows, Which Shape", take "Competing in the Age of AI" (module 2 of AI Strategy & Implementation). Afterwards, continue with "Build, Buy, or Partner".

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