Case Study
Generative AI Systems Design
Deploy citation-backed copilots with rigorous retrieval contracts, ensuring answers are verifiable, permissioned, and resistant to hallucinations.
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AI StrategyCase Study
Value Discovery & Portfolio
Prioritize GenAI investments with defensible stop criteria and risk-aware gating, using resources on initiatives that can scale.
Executive Outcome
01
A prioritized portfolio of GenAI initiatives with explicit value hypotheses, constraints, and stop criteria.
02
Decision clarity: which initiatives to scale, which to pause, and which to retire—based on value, feasibility, and risk.
03
Operational shift: from ad hoc experimentation to a governed intake and investment process with consistent evaluation standards.
Engagement focus
Decision readiness and portfolio governance for scalable GenAI investment.
Context
In regulated enterprises, GenAI demand grows faster than the organization's ability to evaluate feasibility, risk, and operating cost. A portfolio approach was needed to separate investable initiatives from low-signal demand and to establish decision rights for scaling.
The Challenge
- 01High volume of requests with inconsistent quality and unclear business ownership.
- 02Pilots progressing without a repeatable path to production, creating sunk cost and reputational risk.
- 03Limited visibility into feasibility constraints, risk exposure, and operational readiness until late stages.
Approach
- →A standardized intake and scoring framework covering value hypothesis, feasibility constraints, and risk signals.
- →A pre-scale review step to surface security and compliance gaps early, with remediation actions defined before expansion.
- →Clear stop criteria, exit rules, and investment horizons to prevent low-signal initiatives from consuming disproportionate resources.
Key Considerations
- Speed of intake vs. assessment rigor: optimised for fast triage with deeper review reserved for shortlisted candidates.
- Central oversight vs. local innovation: enabled federated ideation with centralized prioritization and governance.
Alternatives Considered
- ✕Ad-hoc funding decisions: rejected due to inconsistent outcomes and poor comparability across initiatives.
- ✕Pure ROI-only ranking: rejected because it underweights feasibility constraints and risk/operability factors.
Representative Artifacts
01Use Case Portfolio Dashboard
02Feasibility & Risk Scoring Matrix
03Investment Decision Memo Template
04Stop Criteria and Exit Rules
Acceptance Criteria
All initiatives evaluated against a common value/feasibility/risk taxonomy.
Investment allocation reflects explicit horizons and scaling conditions, not pilot momentum.
Low-signal initiatives are deprioritized early, with documented rationale and clear ownership.
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