What is 'skills intelligence' and how will it lead to economic resilience?

“Skills are the new currency.”

Perhaps you’ve heard this phrase recently in boardrooms, conferences or policy discussions. It’s a concise way to convey how vital competencies have become in today’s rapidly evolving world. But as we rethink what it takes to build resilient, future-ready economies, it’s worth asking whether this metaphor takes us far enough.

Currency, by its nature, is transactional. It fluctuates in value, depends on demand and is ultimately a medium of exchange. But skills, if they are to drive resilience, adaptability and inclusive growth, must be seen through a different lens – not as commodities to be traded, but as infrastructure that supports, anticipates and enables the growth of resilient, future-ready economies.

Just as roads, broadband and power grids form the foundation of a thriving society, skills form the infrastructure of a resilient economy. They support innovation, enable mobility and power entrepreneurial ecosystems. As the World Economic Forum convenes its Annual Meeting of the New Champions 2025 around the theme of “Entrepreneurship for a New Era,” it’s clear that treating skills as infrastructure is essential.

And like all infrastructure, the systems that deliver skills must evolve to meet rising and shifting demands. Static taxonomies and outdated frameworks can no longer keep pace with the speed of economic transformation. That’s where skills intelligence comes in via the strategic use of artificial intelligence (AI) and machine learning to collect, analyse and translate workforce data into actionable insights.

This isn’t a future vision, it’s happening now. For governments and policy-makers, embedding skills intelligence into national frameworks is the upgrade needed to design agile, data-informed strategies that can withstand today’s disruptions and shape tomorrow’s opportunities.

The Future of Jobs Report 2025 highlights the significant shifts that are transforming the global workforce:

Skills gaps are today’s defining workforce challenge. Traditionally, we’ve excelled at identifying these gaps through surveys and assessments. But we must ensure our current methods are truly preparing individuals and economies to adapt and succeed, rather than merely diagnosing problems without delivering meaningful solutions.

To do this, we must move from skills identification to skills empowerment. This means shifting from highlighting deficiencies to actively building capabilities. Using advanced AI and machine learning, skills intelligence can transform fragmented data into actionable insights, empowering individuals, organizations and economies to adapt rapidly and effectively.

This is how skills intelligence becomes essential infrastructure – an investment that garners an immediate return and sets the foundation for long-term economic growth and societal wellbeing.

Government-led skills classification systems, such as O*NET in the US, ESCO in Europe, and Canada’s NOC, provide a foundational understanding of skills and occupations for their respective labour markets. These taxonomies (structured frameworks for defining and organizing skills) are widely used by policy-makers, educators and private sector leaders to shape workforce strategies, design training programmes and inform labour market policies.

But these frameworks were designed in an era when workplace dynamics evolved slowly and predictably. Today, the pace of workforce transformation is rapid and exponential, making static, periodically updated systems increasingly insufficient.

To navigate this new reality, we must transition from static frameworks to intelligent, responsive skills infrastructures. Integrating AI-powered skills intelligence into national systems allows governments to dynamically define, measure and adapt to workforce needs in real-time.

This is already underway. In 2022, the O*NET and ESCO systems created a "crosswalk" to map skills between their frameworks. This has opened the door to broader integration across national and regional labour market systems, unlocking real-time services like job matching, targeted reskilling and upskilling, better training alignment and sharper labour market analytics. This is a game changer for public and private stakeholders alike.

Recognizing the urgency for interconnected skills frameworks, the WEF’s Global Skills Taxonomy Adoption Toolkit 2025 offers a practical roadmap for governments, businesses and education leaders. Just as physical infrastructure connects communities and supports growth, this toolkit calls for aligned, collaborative systems to tackle labour shortages and support workforce transformation at scale.

It outlines practical, near-term actions, such as standardizing how skills are verified, modernizing job descriptions to reflect transferable capabilities and embedding real-time skills tracking into national systems. These aren’t future ideals, they’re available now. But the potential is far-reaching.

Using skills intelligence, governments can identify “proximity skills”, which are adjacent or easily trainable capabilities that help workers pivot into emerging roles. AI-powered platforms can then match individuals to new opportunities with greater speed and accuracy. The most advanced systems go a step further, using validated skills data – reliable, verified evidence of what people can actually do.

This adds a new layer of trust and utility to workforce planning, making it possible to direct talent where it’s needed most, both within and across borders. In an era of fundamental economic transformation, validated skills will be essential to entrepreneurial solutions and innovation-driven growth.

As we look to a new era of entrepreneurship, the need to reimagine our approach to human potential is clear. The phrase “skills are the new currency” must evolve. Rather than treating skills as transactional units, it’s time to make them the foundation of the systems that drive innovation, resilience and inclusive growth.

AI-powered skills intelligence is at the centre of this evolution. Open, real-time and interoperable platforms can turn fragmented data into dynamic insights about skills. This will give policy-makers, educators and employers the tools to build agile, future-ready talent systems.