The Hidden Economy of Free Learning

Why It Is Time to Start Measuring Learning, Not Just Education. The Future of Learning Series 

Governments can tell us how much they spend on education. They can measure school enrolment, university participation and graduation rates. But there is one question almost nobody asks: what is the economic value of the learning that actually takes place?

The Hidden Economy of Free Learning

When economists measure a nation’s prosperity, they measure production. When governments evaluate education, they measure spending. When businesses assess performance, they measure productivity. Yet in an economy increasingly driven by knowledge, there remains one remarkable blind spot. We rarely attempt to measure the value of learning itself.

This question sits comfortably alongside initiatives such as the World Bank’s Human Capital Project, which argues that the knowledge and skills accumulated by people are among the most important drivers of long-term economic growth. What remains less well understood is how societies should measure the value of new learning as it is continuously created throughout adult life.

That omission mattered less when education was largely confined to schools, universities and employer-funded training programmes.Today, however, learning has moved well beyond the classroom. Millions of adults now acquire workplace skills through AI assistants, YouTube tutorials, free online courses, employer learning platforms, professional communities and industry certification programmes. Whether learning Excel through a YouTube video, completing a Google Career Certificate, using Microsoft Learn, asking an AI assistant to explain Python code or graduating from a structured online course, lifelong learning has become an everyday activity for much of the global workforce.

Much of that learning happens independently, often outside formal education systems and without public funding. It represents a vast investment of human time. Increasingly, it may also represent a significant, yet largely invisible, contribution to national productivity. Taken together, these developments are creating something much larger than any individual platform or technology.

Artificial intelligence provides instant answers. YouTube demonstrates practical skills. Google, Microsoft and other technology companies offer professional certifications. Platforms such as Alison provide structured courses, assessment and recognised credentials. Employers increasingly supplement traditional training with digital learning resources available anytime and anywhere.

Collectively, these different forms of learning are beginning to form what might reasonably be described as a new employability infrastructure. The scale of that infrastructure is already enormous. YouTube alone reports that users watch more than one billion hours of video every day worldwide. While Google does not publish how many of those hours are educational or workplace-related, instructional content is widely recognised as one of the platform’s largest categories. Alongside AI assistants, professional certification programmes from companies such as Google and Microsoft, structured learning platforms such as Alison and countless specialist providers, this represents an unprecedented global ecosystem of continuous learning.
Unlike roads, broadband or transport networks, this infrastructure has not been planned or funded by governments. It has emerged organically through thousands of organisations helping people continuously acquire new knowledge and workplace skills throughout their careers.

Like any infrastructure, its value lies not in any single component, but in the opportunities it creates. The challenge is that, while governments routinely measure investment in physical infrastructure, almost nobody attempts to measure the value being created by this new infrastructure of learning.

From measuring education to measuring learning

For decades, governments have rightly focused on access to education. How many children attend school? How many students enter higher education? How much is spent on training? These remain essential measures, but they tell us relatively little about the quantity of learning that has actually occurred. Unlike informal learning through AI or video, structured learning platforms can measure not only enrollment, but progression, assessment, completion and cumulative hours of successful learning.

Unlike traditional education systems, they can record not only enrollment, but progression, assessment, completion and cumulative hours of successful learning. That creates the possibility of measuring learning in ways that were previously impossible. The challenge then becomes an economic one. If learning creates value, how might that value reasonably be estimated?

Measuring what markets do not price

Economists have long faced this problem. Many activities generate substantial public value despite having no direct market price. These include Environmental assets, Volunteer work, Household labour and Public health. In each case economists use carefully constructed proxy measures to estimate economic contribution. Education presents a similar challenge.

Although formal education has clear market costs, much lifelong learning—particularly free digital learning—takes place outside traditional economic transactions. That does not mean it has no value. Economists frequently use proxy measures to estimate the value of activities that are not directly priced in markets. A hazard in trying to analyze job market outcomes and statistics is that few people who have engaged with a recruiter want to talk to them once they get that coveted job and hence why all the more, the value of the learning itself might be considered.

Why completed learning matters

One of the criticisms often levelled at digital education is that enrolment figures tell only part of the story. Signing up for a course is easy. Completing it requires commitment. For that reason, completed learning may offer a more meaningful measure of educational impact than registrations alone. Hours successfully completed after assessment provide evidence that learners have engaged with material rather than merely expressing an intention to learn. From an economic perspective, completed learning also provides a practical unit of measurement.

Just as economists value infrastructure by the services it provides rather than the plans drawn to build it, learning may be more appropriately valued by what has actually been completed than by what was simply made available.

This is one reason structured learning platforms remain important despite the rise of AI. AI and instructional video are extraordinarily effective at helping people answer questions or solve immediate problems. Structured learning is different. It develops competence through progression, assessment and reflection, creating evidence that learning has genuinely taken place.

A case study in measuring social value

One organisation whose data illustrates both the scale and the measurability of this hidden learning economy is the Irish-founded learning platform Alison. Since launching in 2007 with the mission of providing free access to workplace-relevant education, Alison has grown into one of the world’s largest free online learning platforms.Today the platform reports

• More than 53 million registered learners
• More than 15 million graduates
• More than 126 million completed hours of learning
• Learners from virtually every country in the world

Unlike traditional education statistics, these figures capture learning that has largely taken place voluntarily, outside formal institutions and often alongside employment.The next question naturally follows. What is the economic value of those completed learning hours? One approach is to estimate the replacement cost of equivalent workplace learning. Corporate training programmes, government workforce initiatives and publicly funded digital education schemes all provide benchmarks for the economic value of completed training.

Using conservative estimates derived from publicly available workforce training programmes across different regions, Alison estimates the cumulative social value of completed learning delivered through its platform now exceeds €2.5 billion (See Calculation Figure 1) over its lifetime. Importantly, this is not presented as revenue created by the platform. Nor is it an estimate of future earnings generated by learners. Rather, it is an estimate of the economic value of completed learning itself—the value that would likely have been incurred had equivalent structured workplace learning been delivered through conventional funded programmes. Whether future research refines that estimate upwards or downwards, the broader point remains. Large-scale free learning creates measurable economic value. The challenge is that almost nobody is measuring it.

The global picture

The implications become even more striking when viewed geographically. While Alison has significant learner communities in developed economies including the United States, the United Kingdom and Canada, some of its largest learning populations are found across Africa and Asia. Countries such as Nigeria, South Africa, Kenya, Ghana, Pakistan and Egypt now account for millions of hours of completed learning.In many of these economies, access to affordable professional development remains constrained by cost.

Free digital learning therefore represents not simply educational opportunity, but workforce infrastructure. Each completed hour contributes incrementally to national human capital. Unlike roads or power stations, this infrastructure is largely invisible. Yet it may prove equally important to long-term economic development. This reflects another important shift. Historically, access to professional development depended largely on employers or higher education institutions. Today, much of that opportunity is available directly to individuals, often free of charge and accessible from anywhere with an internet connection.

(Figure 1: Alison – Social Impact / Value of Free Learning (2007-2026)

Unlike much informal digital learning, these figures represent structured learning that has been completed rather than merely started or viewed. That distinction makes Alison’s dataset unusually valuable for researchers attempting to understand the real scale of lifelong workplace learning.

An invisible asset

Perhaps the most remarkable aspect of the digital learning revolution is that its success has been measured largely through platform metrics.

The digital economy has become remarkably good at measuring attention. We know how many people watched a video, clicked a link, downloaded an app or registered for a course. We remain surprisingly poor, however, at measuring something far more valuable: how much people have actually learned. Far less attention has been given to learning as an economic asset – but that is beginning to change. As artificial intelligence reshapes labour markets and technological change shortens the lifespan of professional skills, economies will increasingly depend upon adults acquiring new knowledge throughout their working lives. Learning itself becomes infrastructure.The ability to measure its contribution therefore becomes an economic necessity rather than an academic curiosity.

Looking beyond expenditure

As artificial intelligence accelerates the pace of economic change, employability will increasingly depend upon continuous learning rather than one-off qualifications. Perhaps the next challenge for policymakers is not simply to measure how much societies spend on education, but how much capability they create. Because in the knowledge economy, what ultimately drives prosperity is not education that is funded. It is learning that happens.

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