# AI portfolio prioritization steering brief

## Portfolio choices

Present the top initiatives, current score, funding request, operating value, delivery risk, required controls, dependencies, and expected reusable learning. Separate high-value ideas that are not ready from lower-risk projects that build reusable platform capability.

## Executive decision

Ask for one decision per initiative: fund, discover, hold, scale, or retire. Each funded initiative needs an owner, evidence gate, date, and failure condition.

## Follow-up

Re-score the portfolio after discovery or pilot evidence. Retire initiatives that do not produce a credible path to value, safety, adoption, and operating ownership.