Cambridge
Academy
In London

Introduction

AI can help initiative teams prioritize faster by organizing ideas, scoring initiatives against criteria, and highlighting trade-offs and capacity constraints. This practical program equips initiative advisors with simple AI-supported methods to build prioritization models, produce decision-ready shortlists, and maintain transparency and governance—while keeping human judgment and validation at the center.

Course Objectives

By the end of this course, participants will be able to:

·        Use AI to structure initiative lists and standardize descriptions

·        Build simple scoring criteria and weighting models

·        Use AI to compare options and highlight trade-offs

·        Create decision-ready prioritization packs and shortlists

·        Apply safe-use rules and quality checks

Target Audience

This course is designed for:

·        Initiatives advisors and coordinators

·        Strategy execution and PMO support teams

·        Performance and reporting specialists

·        Program/project teams shaping portfolios

·        Teams supporting executive decision forums

Course Outlines

Day 1: AI Basics for Prioritization

·        Where AI helps in prioritization

·        AI limits and verification needs

·        Prompting basics for structured outputs

·        Safe use and confidentiality

·        Activity: Build a prioritization prompt list 

Day 2: Structuring Initiatives for Scoring

·        Standard initiative one-pager fields

·        Clean problem statements and outcomes

·        Defining assumptions and scope

·        Grouping initiatives by theme

·        Workshop: Create a standardized initiative list 

Day 3: Scoring Models and Weighting

·        Choosing criteria (value, effort, risk)

·        Setting weights and thresholds

·        Using AI to suggest scoring inputs (with checks)

·        Ranking and sensitivity basics

·        Activity: Build a simple scoring sheet

Day 4: Trade-offs and Decision Packs

·        Portfolio balance (quick view)

·        Capacity and dependency notes

·        AI-assisted decision briefs and summaries

·        Handling conflicts and edge cases

·        Case study: Prioritization meeting simulation

Day 5: Governance and Adoption

·        Approval workflow and documentation

·        Quality checks and audit trail

·        Updating scores and re-prioritizing

·        Simple KPIs for prioritization process

·        Final project: AI prioritization playbook