Implementation guide
Scale AI with Portfolio Governance and ROI Discipline
Detailed training workflow for Scale AI with Portfolio Governance and ROI Discipline in Playbooks: Core Systems.
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Guided walkthrough
The Goal: move from isolated wins to a sustainable operating model with clear ownership and measurable value. CoE Charter Define mission, scope, decision rights, and team composition. Portfolio Registry Track use cases by stage: proposed, pilot, production, retired. KPI Stack Measure adoption, quality, risk incidents, and realized business impact. Monthly Governance Review promotions, shutdowns, budget shifts, and risk exceptions.
Advanced implementation notes
Portfolio Governance Engine Operating Cadence Run weekly delivery review, monthly governance board, and quarterly strategy reset. Stage Gates Enforce objective criteria to move use cases from pilot to production. Value Realization Compare forecasted ROI vs realized ROI and re-prioritize aggressively. Risk Integration Embed compliance incidents, audit findings, and mitigation plans into portfolio decisions. Capability Roadmap Invest in shared enablers: template library, evaluation harness, approval workflows, and training cohorts. CoE Monthly Dashboard -
Proposed use cases: - Pilot use cases: - Production use cases: - Retired use cases: - Avg quality score: - Hours saved: - Realized ROI: - Risk incidents: - Decisions required: Shut down low-value pilots early to free capacity for high-impact work. Assign a business sponsor for every production use case. Report realized outcomes, not only activity metrics. Do not let each department create independent standards. Do not keep zombie pilots with no owner or KPI. Do not approve budget expansion without evidence of realized value.