Resolving Workforce Skills Gaps with AI-Powered Insights | MIT Center for Information Systems Research

Talent Management
Tags:

If you find value in content like this, sign up for my Talent Edge Weekly newsletter.

This article presents a case study detailing how Johnson & Johnson (J&J) leveraged artificial intelligence (AI) to assess its workforce’s current skills and their alignment with future requirements for organizational success. The organization followed a three-step process:

  1. Developing a skills taxonomy by identifying skills crucial for future business plans, initially piloted within J&J’s Digital Talent team, resulting in 41 skills across 11 capability areas.
  2. Collecting skills evidence by selecting and preparing employee data sources to analyze. The company used four data sources: the organization’s HR information system, recruiting database, learning management system, and one of its project management platforms.
  3. Conduct a skills assessment, for which a machine learning model is trained to measure the skills proficiencies of each employee. Proficiency scores ranged from 0 (no skill detected) to 5 (thought leadership).

J&J’s AI-driven skills inference process is exclusively utilized to offer personalized career development paths for employees and, at an aggregate level, to assist leaders in strategic workforce planning.

For more on this topic, check out my book chapter in Strategic Workforce Planning: Best Practices and Emerging Directions (The Society for Industrial and Organizational Psychology Professional Practice Series—published 3/29/24).