Module 2 • 22 min
Why AI Initiatives Succeed, Stall, or Fail
Recognize the failure patterns that prevent AI work from reaching production.Core Concept
Most initiatives stall when they begin with a tool, skip readiness work, or never define a measurable business outcome.
This choice influences the value case, implementation effort, governance requirements, and the organization’s ability to operate the system after launch.
How to Apply the Framework
A production-minded initiative sets scope, baseline, governance, and ownership before the pilot creates false confidence.
Use a current workflow, its measurable baseline, and the real people and systems involved. A strategy that works only in a simplified example is not yet a decision-ready operating plan.
Decision Checklist
- State the business outcome and the bounded workflow this decision will improve.
- Identify the accountable business owner, technical owner, and required human reviewer.
- Confirm the evidence, dependencies, controls, and decision gate required before moving forward.
Worked Decision Scenario
A business unit funds a chatbot pilot before defining the source data, the owner of the workflow, or the metric that would prove value. The pilot becomes difficult to judge because every issue is framed as a technology problem.
The sponsor resets the work around one measurable support workflow, a named owner, and a readiness gate. The new plan can expose a real constraint early instead of discovering it after months of build effort.
Apply it
Working Exercise
Which failure pattern is most likely in your organization?
Saved locally for this review prototype. Your response will become private account data when the approved course backend is connected.