The Challenge

A global education organization needed a skills framework designed for the realities of graduate education. Existing taxonomies — often based on generic labor market data — were missing critical skills, including irrelevant ones, and failed to reflect how skills are actually learned, described, and applied in practice.

Our Approach

Using the TRACE AI System, we built a living skills framework grounded in real human behavior. The model learns continuously, it captures new skills as they emerge and tracks shifts over time.

Mapped how skills are expressed and developed – Drew from a broader and more varied set of data sources than existing frameworks
Connected learning to career paths – Linked skills to educational programs and career outcomes, revealing the actual pathways people take from study to work, and tracking trajectories over time.
Designed for adaptability – Built the framework to evolve with the market, so it remains relevant as industries change and new skills emerge.

The Outcome

The result will replace a generic, third-party taxonomy with a transparent, domain-specific model that powers real-time applications. Schools, employers, and learners will be able to explore the real connections between education and career success — making it easier to plan careers, align programs with market needs, and match people to the right opportunities with unprecedented precision.