Most AI-for-PM training stops at “here are twelve prompts.” This course teaches the workflow: how evidence enters an AI system, what it is allowed to decide, how the output gets verified, and what you can defend to a stakeholder, a legal reviewer, or a regulator.
You will watch a fabricated competitor price get planted in a source, pulled into a research query, repeated with a citation attached, and passed by four competent people before anybody notices. You will watch a synthetic user panel enthusiastically approve a feature that real ward managers refuse in the first ten minutes of the first session. You will watch prioritisation scores move across three identical runs. These lessons land as demonstrations and evaporate as bullet points.
What makes this different:
- Honest about synthetic data. An entire section on where generated respondents are defensible and where they are not, backed by the finding that around 97% of researchers now use AI somewhere while only about 8% regularly use synthetic-respondent tools.
- Traceability as a discipline. Every insight links to a real quote with a source ID. Every market claim carries two independent sources.
- Regulation that is current. What binds you now under EU AI Act Article 50, versus what moved to December 2027 and August 2028.
- A single continuous case. Brightline Software, a 480-person B2B healthcare scheduling company, carries a story that moves forward every section — from an eleven-week cycle to three weeks.
