From Measurement to Action: A Learning Engineering Approach to AI-Powered Assessment for Human Power Skills Development

As AI systems transform work at scale, human “power skills”—including creative thinking, communication, collaboration, leadership, analytical reasoning, productivity, and AI fluency—are increasingly critical to employability and long-term success. Yet these skills remain difficult to measure rigorously and to develop systematically. This paper is explicitly grounded in Learning Engineering and demonstrates how a nested Learning Engineering cycle—spanning challenge definition, creation, implementation, and investigation—can be embedded within a novel AI-enabled assessment system. Building on prior large-scale assessments of collaborative problem solving and creative thinking, adaptive learning research, and agentic AI, the Ignis AI PowerSkillsAssessment™ integrates evidence-centered design, generative AI, Bayesian proficiency estimation, and fairness-aware modeling into a unified operational framework. We describe the construct model, task design, scoring architecture, and early pilot results with professionals and managers, illustrating how learning engineering can translate insights from cognitive science and psychometrics into scalable, actionable tools for talent development in the AI era.