University AI Initiative Portfolio and Academic Impact Review

Review a university's AI initiative portfolio to determine which activities have credible academic or institutional value and which require redesign, consolidation, evidence development or closure.

## Portfolio inputs

Initiative register, owners, users and lifecycle states:
{{initiative_register}}

Outcome, adoption, cost and operational evidence:
{{outcome_cost_and_adoption_evidence}}

Risk, inclusion, data, control and dependency evidence:
{{risk_and_dependency_evidence}}

Institutional mission, constraints and decision authority:
{{mission_constraints_and_authority}}

## Portfolio evidence rules

- Separate approved objective, observed result, initiative-owner claim, financial estimate, inference, assumption, conflict, missing information and unresolved uncertainty.
- Do not invent costs, saved time, learning gains, research impact, adoption, risk acceptance, approvals or causal attribution.
- Distinguish activity and output from outcome and impact. Do not treat licences purchased, users registered or content generated as realized value.
- Compare initiatives using shared decision dimensions without forcing unlike teaching, research and administrative outcomes into one opaque score.
- Surface distributional effects, accessibility, staff/student burden, data rights and who bears risk or unpaid review work.
- This review prepares a decision pack. Portfolio allocation, employment, academic, legal and risk decisions remain with the named governing owners.
- Make cost calculations reproducible by recording source values, units, time periods, allocation rules, formulas and sensitivity assumptions. Label shared-cost allocation and causal attribution limits explicitly, and require finance validation before use.
- Aggregate learner and staff evidence and suppress small cells where disclosure or re-identification risk exists. Do not infer individual performance from portfolio data.

## Review method

1. Normalize the portfolio: initiative purpose, sponsor, affected group, stage, dependencies, committed resources, decision date and claimed outcome.
2. Build an evidence bridge from resources and activity to observable outputs, outcomes and mission contribution. Record alternative explanations and counterfactual evidence where available.
3. Reconcile cost, including licences, infrastructure, integration, support, review, training, remediation, compliance and exit. Provide reproducible formulas, units and ranges, state causal and allocation limits, and flag all figures pending finance validation.
4. Assess adoption quality: intended versus actual use, workflow displacement or augmentation, friction, exclusion, work shifted to other roles and persistence over time.
5. Map material privacy, security, academic integrity, research integrity, accessibility, equity, vendor and operational dependencies with current control evidence.
6. Identify overlap, shared infrastructure, incompatible approaches, duplicated evaluation, concentration risk and opportunities for responsible consolidation.
7. Compare each initiative against explicit `Scale`, `Redesign`, `Hold` and `Stop` evidence gates. Frame each result as evidence supporting consideration by authorized owners, not a decision made by AI. Do not manufacture a ranking when outcome types are not comparable.
8. Sequence decisions and dependencies, including evidence work, consultation, contractual windows, continuity and reversible exit.

## Output contract: University AI Portfolio and Impact Dossier

Provide:

1. **Portfolio register**: initiative, sponsor, purpose, users, stage, cost range, dependencies and next decision.
2. **Academic impact evidence bridge**: input, activity, output, observed outcome, mission contribution, source, attribution limit and confidence.
3. **Adoption and burden map**: beneficiary, actual use, friction, review workload, excluded group and corrective owner.
4. **Risk and control evidence map**: exposure, affected group, evidence, control, gap, accepted owner and review date.
5. **Duplication and dependency map**: shared job, overlapping asset, concentration, consolidation option, transition risk and constraint.
6. **Initiative disposition cards**: evidence supporting consideration of `Scale`, `Redesign`, `Hold`, `Stop`, or `Insufficient evidence`, with gate evidence, conditions, dissent and authorized decision owner.
7. **Portfolio sequence**: immediate reversible action, dependent decision, contractual/academic timing, owner and completion evidence.
8. **Governing-body brief**: decisions requested, evidence strength, unresolved uncertainty, distributional impact and matters outside this review.

## Verification and completion

Complete only when every initiative has an owner and lifecycle state; value claims trace to supplied evidence; full cost and shifted burden are visible; risks and dependencies are mapped; dispositions use explicit gates; and the governing decision remains with authorized owners.

If the initiative register, outcome data, costs or decision rights are materially incomplete, issue an evidence-development plan instead of a portfolio recommendation. Refuse to fabricate impact, approve investment, make employment decisions or present suggested dispositions as adopted policy.