The rapid adoption of AI has sparked urgent conversations about the future of education and work. Many industries, employers, educators, policymakers and global organizations are asking the same question: "What human competencies will matter most in the age of AI?"

The challenge is no longer simply identifying broad skills that seem important. It is determining which human competencies remain distinct and uniquely valuable, how their meaning and demonstration are changing in AI-mediated learning and work, and whether they can be measured with enough rigor to support meaningful decisions about learning, hiring, credentialing, advancement and mobility.

This question sits at the intersection of education, workforce development, assessment innovation and human progress, making it one of the most pressing research questions of our time.

Conversations about the future of work increasingly emphasize the importance of human competencies. Educational systems, employers, governments and international organizations are prioritizing competencies such as communication, collaboration, problem solving, critical thinking, adaptability, and lifelong learning. These competencies are critical for navigating a world in which routine tasks are increasingly automated, and work is becoming more technology enabled.

Many existing frameworks identify skills believed to be important for future success, yet few establish whether those competencies are truly distinct, measurable, developable or predictive of meaningful educational and workforce outcomes. As a result, educators, employers, learners and policymakers are often left with important questions and limited evidence to guide decisions.

As AI reshapes both learning and work, it is changing not only which competencies matter, but also how those competencies are expressed, developed and applied. In addition, entirely new competencies may emerge.

For example, we ask questions like these:

• What does human-AI collaboration look like?
• How do individuals learn to evaluate AI-generated information, calibrate trust in AI systems and maintain accountability for decisions made alongside AI?

These questions influence how students prepare for future careers, how workers adapt to changing occupations and how organizations identify and develop talent. AI also changes what counts as evidence of human performance. A final product may reflect joint human-AI work, so educators, employers, and assessment developers need better ways to observe, interpret and validate the human contribution within AI-mediated tasks.

To have real value for education and workforce decisions, competencies must be defined clearly, measured reliably and linked to meaningful outcomes. We need evidence showing whether a competency is distinct from other constructs, how it develops over time, whether it can be strengthened through learning experiences and how it contributes to success across different contexts.

This is where ETS is uniquely positioned to contribute. Through decades of measurement science, ETS has helped educators, employers and learners make informed decisions about readiness, potential and opportunity. With expertise in construct validity, psychometrics and readiness measurement, ETS is prepared to address a critical question: Which claims about human competencies can be trusted, and how do we know?

The Center for Advancing Human Competencies was established to build the scientific foundation for understanding human competencies in an AI-shaped world. Under Lydia Liu’s leadership, the Center will focus on turning broad claims about human competencies into validated constructs, usable evidence and practical guidance for education and workforce systems. Its focus is straightforward but ambitious: identify which competencies matter most, determine how they develop and generate the evidence required to support trusted decisions across education and work.

The Center’s FY27 portfolio will build this evidence base through three connected lines of work. First, it will define and prioritize human competencies in the AI era, including competencies involved in human-AI collaboration. Second, it will examine workforce readiness across education-to-work pathways, including college-to-workforce, high-school-to-workforce and CTE-based occupational mobility. Third, it will investigate how human competencies are embedded in STEM disciplines and how they can be made visible through authentic mathematics and science assessment contexts.

Together, these programs distinguish the Center from efforts that simply list future-ready skills. The Center will use measurement science to clarify construct definitions, develop evidence models, test how competencies are demonstrated across contexts and translate findings into tools, frameworks and guidance that can support better decisions for learners, educators, employers and policymakers.

The challenges associated with defining and validating human competencies are not limited to any one country or labor market.

The Center is being designed with a global footprint, drawing on partnerships and expertise from across North America, Europe, Asia and Latin America to help ensure that human competencies are defined and validated across diverse educational systems, cultures and labor markets.

Validating competencies globally is essential if evidence of capability is to support mobility and opportunity across borders, industries and stages of life.

The growing demand for human competencies has created a paradox. Employers, educators and policymakers increasingly rely on these competencies to inform decisions about readiness and success, yet the underlying science has not kept pace with the claims being made. At a time when AI is reshaping both learning and work, that gap has become impossible to ignore.

If human competencies are increasingly being used to inform decisions about education, careers and opportunity, they must be grounded in rigorous science. We need a stronger understanding of which competencies matter, how they develop, what evidence can validly represent them and how they contribute to meaningful outcomes. The Center for Advancing Human Competencies is being launched to answer those questions and to make evidence about human competencies more usable across education, work and policy.

At a time when AI is transforming what machines can do, the Center will focus on what people can do, how those competencies can be recognized and how validated evidence can expand opportunity, readiness and mobility.