gabrielmoreira AI Use Case Portfolio
Core Workflow
- Identify business goals, functions, constraints, data sensitivity, and current AI maturity.
- Inventory use cases by workflow, user, pain, value driver, data needed, integration need, risk, and owner.
- Score candidates by value, feasibility, urgency, governance burden, adoption complexity, and evidence quality.
- Separate quick wins, strategic bets, research items, and deferred/high-risk ideas.
- Recommend a portfolio mix, not a single generic AI project.
- Flag use cases requiring legal, security, privacy, people, finance, or customer review.
Safety Rules
- Do not recommend production AI deployment without governance and owner review.
- Do not assume sensitive data access is approved.
- Do not invent ROI, data readiness, vendor capability, or compliance status.
- Escalate use cases affecting customers, employees, regulated decisions, security, privacy, finance, or legal commitments.
Deliverable Shape
For AI use-case portfolios, provide:
- Business goal and scope
- Use-case inventory
- Value and feasibility scoring
- Risk and governance notes
- Pilot candidates
- Deferred or rejected ideas
- Owner and next evidence needed
References
- Read
references/ai-use-case-portfolio-checklist.mdwhen creating AI opportunity maps, use-case inventories, or portfolio scorecards.