# AI portfolio prioritization kit

Use this kit to rank AI opportunities by operating value, feasibility, risk, readiness, and reusable learning. The goal is to make portfolio decisions explicit enough for executives to fund, pause, scale, or retire initiatives with evidence.

## What it includes

- A scorecard for value, feasibility, risk, data readiness, control maturity, adoption effort, and learning leverage.
- A roadmap model for initiative ownership, funding stage, dependencies, release gate, and expected outcome.
- A structured prioritization model.
- A steering brief for portfolio tradeoffs and funding decisions.
- A risk map for sequencing by regulatory exposure, operational dependency, data readiness, and failure impact.

## How to use it

Score initiatives before funding delivery work. Favor projects that create reusable controls, data products, evaluation sets, or operating patterns. Re-score after discovery, pilot, and production evidence so the roadmap reflects what the organization has learned.