Developing a Digital-First Workforce: AI-Driven Skills Enablement at Johnson & Johnson
Learning Objectives
- Explain how J&J translated the strategic plans of its operating companies into a defined skills agenda before adopting any AI tooling.
- Assess how J&J’s data-source criteria and its governed HR Data Hub determined what the skills-inference model could learn.
- Compare AI-inferred skills assessment at J&J with traditional instruments: functional competency models, job titles, self-assessments, and manager ratings.
- Design a stakeholder engagement approach for AI in talent management, drawing on the distinct value propositions J&J crafted for employees, managers, and senior leaders.
- Analyze how J&J used employee and manager ratings as a human check on machine-inferred proficiency, and why model retraining lowered some scores while raising overall accuracy.
- Evaluate the evidence J&J assembled for MySkills’s impact and its acceleration of skills-based talent management.
Abstract
In 2020, Johnson & Johnson (J&J) was on mission to transform the trajectory of human health—a mission increasingly driven by emerging technology and a growth in data and computing requirements. To realize its mission, each of J&J’s more than 150,000 employees would need to have the skills to use new technologies to reimagine business processes, develop new offerings, or both. To assess employees’ current skill levels, identify gaps, and offer development and career opportunities, J&J’s Technology group created MySkills, a talent development platform powered by machine learning. This case outlines the steps that J&J took to establish MySkills, and how this platform helped develop a digital-first workforce.
Appropriate for the Following Course(s)
artificial intelligence, talent management, responsible AI and data privacy, change management, and data management and analytics
THERE IS NO TEACHING NOTE FOR THIS CASE STUDY.