Use-Case Portfolio Review Loop

By Juan Beltrán — personal website on AI and digital growth for complex B2B industries.

Which AI ideas should we fund, fix, pause, or stop? Use this when the AI backlog has become a long list of interesting ideas and leadership needs a smaller set of decisions. Use-Case Portfolio Review Loop Task: Which AI ideas should we fund, fix, pause, or stop? Context: [Paste your notes, excerpts, draft, meeting transcript, CRM fields, proposal text, public research, or examples here.] Context I should provide: - Current AI initiative list - Business owner for each initiative - Value estimate - Data readiness note - Delivery status - Decision requested Useful setup: Paste an initiative list with owner, business goal, current status, estimated value, known blockers, and the decision you need. Why this matters: Use this when the AI backlog has become a long list of interesting ideas and leadership needs a smaller set of decisions. Business problem: AI portfolios become long lists of plausible ideas with no owner, value logic, or kill discipline. Instructions: Act as an enterprise AI portfolio operator. Review the initiatives below. For each one, rewrite the business outcome, identify the evidence level, flag missing ownership or data dependencies, and recommend scale, fix, defer, kill, or merge. End with the three decisions we should make this month and the evidence needed before the next review. Workflow: 1. Normalize the backlog: Rewrite every initiative as an outcome, owner, user, process, and expected value pool. 2. Score the evidence: Separate measured value, plausible value, and vendor-claimed value. 3. Find shared constraints: Identify repeated blockers across data, integration, adoption, governance, and sponsorship. 4. Assign a portfolio decision: Mark each initiative as scale, fix, defer, kill, or merge. 5. Sequence the next month: Fund only the moves that reduce downstream uncertainty or unlock multiple initiatives. Quality bar: - Use only the context in this chat. - If important information is missing, ask for the minimum missing context before giving a final recommendation. - Separate facts from assumptions. - Do not invent customer facts, benchmarks, financial numbers, policy approvals, or system access. - Keep the answer useful for Transformation Lead. Output: A ranked portfolio with clear scale, fix, pause, merge, or stop decisions. - BLUF recommendation or draft. - Evidence from my context. - Assumptions and missing information. - Risks, objections, or failure modes. - Recommended next action, owner, and stop condition. Evidence checklist: - Actual usage or workflow observation - Finance-approved value logic - Named business owner - Known data source - Adoption dependency - Integration dependency Stopping condition: Stop when the portfolio has fewer active initiatives than accountable owners and every funded initiative has a next evidence milestone.

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