AI Product Management and Commercialization

Module 1: AI product opportunity

Interpret the issue through the organization’s processes, information, responsibilities, and risk appetite. Establish the vocabulary, boundaries, stakeholders, and decision context for AI product opportunity.

Convert the analysis into a role-specific executive case with explicit owners and decision gates. Separate established requirements and reliable evidence from untested assumptions about AI product opportunity.

Peer-review feasibility, unintended effects, and the evidence required before approval. Map AI product opportunity to the organization’s current responsibilities, dependencies, and constraints.

Module 2: discovery data and feasibility

Interpret the issue through the organization’s processes, information, responsibilities, and risk appetite. Diagnose the current state of discovery data and feasibility using a structured decision workshop.

Convert the analysis into a role-specific decision workshop with explicit owners and decision gates. Compare alternative methods and select an approach suited to risk, maturity, and scale.

Peer-review feasibility, unintended effects, and the evidence required before approval. Document requirements, owners, decision criteria, and exceptions for discovery data and feasibility.

Module 3: MVP evaluation and risk

Interpret the issue through the organization’s processes, information, responsibilities, and risk appetite. Design the workflow, safeguards, and handoffs required for MVP evaluation and risk.

Convert the analysis into a role-specific strategy roadmap with explicit owners and decision gates. Test normal, failure, and edge-case scenarios before operational adoption.

Peer-review feasibility, unintended effects, and the evidence required before approval. Review the design for security, quality, accessibility, sustainability, or assurance implications as relevant.

Module 4: go-to-market and economics

Interpret the issue through the organization’s processes, information, responsibilities, and risk appetite. Define meaningful measures, evidence, review cadence, and escalation thresholds for go-to-market and economics.

Convert the analysis into a role-specific executive case with explicit owners and decision gates. Investigate performance gaps and separate root causes from symptoms.

Peer-review feasibility, unintended effects, and the evidence required before approval. Plan corrective action, controlled change, and accountable follow-through.

Module 5: Applied AI Product Management and Commercialization Workshop

Interpret the issue through the organization’s processes, information, responsibilities, and risk appetite. Complete a decision workshop that integrates the course decisions around product investment pitch.

Convert the analysis into a role-specific decision workshop with explicit owners and decision gates. Defend recommendations against a realistic stakeholder challenge or scenario.

Peer-review feasibility, unintended effects, and the evidence required before approval. Produce a prioritized workplace action plan with owners, dependencies, and review points.