Description
AI-READY LEAN PRACTITIONER PROGRAM
Most AI training focuses entirely on the tool.
This course focuses on the practitioner. Designed for Lean professionals at any belt level, this program proves that you are already perfectly positioned to use AI responsibly. We will explore how your existing commitment to data, flow, waste reduction, and the gemba translates directly into effective AI use.
Learn how to leverage AI to sharpen your problem framing and process analysis, while ensuring human-centered change remains the driving force behind your improvement work.
PROGRAM DETAILS:
Length: 7.5 hours
Format: Self-directed online learning
Pace: Work at your own pace
Audience: Yellow Belt, Green Belt, Black Belt, or equivalent Lean practitioners
Credential: Digital badge issued through Accredible, valid for 2 years and shareable on LinkedIn
CANCELLATION POLICY:
100% refund within 7 days, less a $75 cancellation fee, if you haven't started the modules.
Cancellations after this 7-day period are not eligible for a refund.
Objectives
By the end of this program, you will be able to:
- Select the right AI type for a given Lean task and explain why it fits.
- Write focused, usable prompts using the CRAFT framework, a structure that aligns directly with the problem-framing discipline Lean practitioners already use.
- Map AI use to each phase of PDCA and identify where practitioner judgement must lead.
- Apply AI to value stream mapping, 5 Whys, A3 documentation, and standard work.
- Detect errors, hallucinations, weak assumptions, and gaps in AI output before acting on it.
- Assess data readiness and identify what needs to be in place before AI can add reliable value.
- Apply a seven-question responsible use checklist to any AI-assisted improvement task.
- Evaluate a predictive analytics output and determine whether it is trustworthy enough to act on.
- Identify bias risks in AI outputs before using AI-assisted recommendations.
- Complete a scenario-based applied exercise while maintaining full practitioner accountability for every output.
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