Project Overview

The AI Chief Workforce Officer Challenge explores how Generative AI can develop executive-level workforce recommendations—and how those recommendations should be evaluated before reaching a CEO.

Drawing on 30+ years of experience in Finance, Budget Planning, Operations, and Human Resources, I apply a methodical, business-focused approach to assess whether AI-generated recommendations are practical, financially sound, operationally realistic, and ready for executive consideration.

The challenge simulates a newly appointed CEO asking for recommendations across a range of workforce issues. I use a methodical evaluation approach to assess each AI recommendation.

Project Objectives

• Evaluate AI-generated workforce recommendations using structured business criteria.
• Assess strategic thinking, business alignment, workforce impact, risk analysis, financial awareness and executive communication.
• Identify assumptions, gaps, and potential weaknesses in AI recommendations.
• Determine whether recommendations would withstand executive-level scrutiny.
• Demonstrate how domain expertise and Generative AI can work together to improve business decision-making, while applying experienced human judgment to evaluate the quality and practicality of the output.

Evaluation Methodology

I used a realistic senior leadership scenario in which a newly appointed CEO requested executive-level workforce recommendations. After identifying 20 realistic workforce issues, I submitted them to the AI to develop formal recommendations. I evaluated the AI-generated recommendations using my 30+ years of experience in Finance, Budget Planning, Operations, and Human Resources to assess their practicality and executive readiness.

Each recommendation was evaluated using a structured, weighted 1–5 scoring rubric across six criteria:

1. Strategic Thinking – Does the recommendation address the core business issue and consider longer-term implications?
2. Business Alignment – Is the recommendation aligned with organizational goals, operational needs, and workforce priorities?
3. Workforce Impact – Does it consider the impact on employees, engagement, and workforce capability?
4. Risk Analysis – Does it identify key implementation risks, and constraints?
5. Financial Awareness – Does it consider costs, and financial trade-offs?
6. Executive Communication – Is the recommendation clear, concise, and appropriate for CEO-level review?

Each criterion was scored from 1 (Does Not Meet) to 5 (Significantly Exceeds), with weighted scores used to determine the overall quality of each recommendation. My evaluation focused on whether the AI-generated recommendations were realistic, actionable, and would withstand executive-level review.