Starting from zero
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AI Implementation Curriculum
A pilot is not a product demonstration. It is a managed learning loop around a meaningful piece of work.
A delivery pathway for turning a promising AI idea into a workflow that people can use, review, improve, and decide whether to scale.
Programme architecture
A curriculum that meets people where they are.
- For
- Business owners, process owners, delivery teams, technology teams, and pilot participants.
- Format
- Co-design sessions, workflow prototyping, implementation support, and retrospectives
- Typical shape
- Pilot design, workflow build, supported launch, and evidence review
Already experimenting
Improve inconsistent pilots by making roles, inputs, quality checks, and learning loops explicit.
Preparing to scale
Create repeatable implementation patterns, governance, and decision points for a growing portfolio.
Sessions and working outcomes
The work is designed to leave something useful behind.
Contain the use case
Name the user, workflow, information boundary, desired change, and the person accountable for the outcome.
Working outcome: A pilot charter.Design the workflow
Map inputs, tool use, human review, exceptions, handoffs, and what happens when an output is not good enough.
Working outcome: A workflow and quality design.Prepare people and controls
Ensure participants know the purpose, boundary, quality standard, and escalation route before launch.
Working outcome: Launch readiness checklist.Pilot in the work
Support the people closest to the workflow, capture friction, and keep the implementation adjustable.
Working outcome: Pilot feedback and improvement log.Review and decide
Evaluate evidence and decide whether to continue, change, pause, or extend the work.
Working outcome: Scale, pause, or redesign decision record.What the organization keeps
Tools, decisions, and practices that can travel into the next phase.
- Pilot charter
- Workflow and review design
- Implementation readiness checklist
- Feedback and improvement log
- Scale decision record
Find the right entry point
Start with a short practical check, then decide the right level of support.
The learning path
Four stages, designed to build on each other.
Contain
Choose a user, workflow, boundary, and outcome that are specific enough to test.
Design
Define inputs, roles, quality checks, exceptions, information boundaries, and a measure of progress.
Pilot
Introduce the change with the people closest to the work and create space for direct feedback.
Learn
Review evidence, improve the workflow, and consciously decide whether to extend, pause, or redesign.
What participants leave with
Work that can continue after the session.
- A contained pilot charter
- Workflow and quality design
- Clear business ownership
- A review cadence for evidence-led scaling decisions
The thesis
The AI Implementation Thesis
Read the point of view behind this curriculum, the decisions it is designed to support, and the practices that make the work durable.
Download thesis outlineFind the right starting point