Learning, Not as we know it - Intellylabs Technologies

In Brief

Our ground-breaking economic modeling uncovers how intelligent technologies will reshape the demand for tasks, skills, and jobs. Today’s education and training systems are not keeping up with the current demand for skills, let alone tomorrow’s new demands. New approaches to learning are needed if businesses are to achieve the growth promised by intelligent technologies. We suggest three remedies: Speed up experiential learning techniques, broaden individuals’ blend of skills, and ensure inclusive access to tomorrow’s skilling solutions.

The race is on

It’s a race between education and technology. As intelligent systems and machines reshape the nature of work, people will need entirely new skill sets.

But the very skills that are growing in importance are not taught in classrooms. They are acquired through practice and experience, often over long periods of time. Some large corporations are experimenting with new lifelong learning methods, but traditional education and learning systems are ineffective and inappropriate for the new skills challenge. Smaller organizations are most at risk if they cannot apply new learning techniques. The potential economic cost is great.

$11.5T is the economic growth driven by intelligent technologies that could be forgone if skill building fails to catch up, across 14 G20 countries.

90% the proportion of worker time will be potentially impacted by intelligent technologies, either through augmentation or automation.

Our analysis shows that failing to close the skills gap could cost China up to 1.7 percentage points from its average annual growth rate in the next 10 years. Mexico and South Africa could lose 1.8 percentage points. Economies with a stronger skills base could still lose big: as much as US$975 billion in the United States and US$264 billion in Germany.

If G20 countries are unable to adapt the supply of skills to meet the needs of the new technological era, they risk forgoing up to US$11.5 trillion in GDP growth over the next 10 years.

How will technology impact skills demand?

Our ground-breaking analysis reveals the relative shift in demand for different kinds of work, based on whether intelligent technologies automate tasks or augment them. We estimate that, overall, 51% of the time worked could be augmented. 38% is automatable.

We have constructed 10 role clusters that make up the world of work. Each role cluster groups occupations that are impacted by intelligent technologies in similar ways. Tasks in the Science & Engineering and the Empathy & Support clusters are most likely to be augmented, as intelligent technology enhances people’s capabilities and the value of the work they do. Physical Manual Labor will be most exposed to automation in the coming decade.

The predominant impact of intelligent technologies will be to augment work

For most roles, augmentation holds great promise. Business and government decisions will determine by how much and by when.

In the US, Empathy and Support workers, such as nurses and psychiatrists, represent the largest single share of employment in the entire economy. Our research highlights that these roles are highly augmentable. Sixty-four percent of their work time could be potentially augmented, and 14 percent might be augmented within the next ten years. As this happens, we can expect an increase in demand for these roles, as much as 1.4 million workers. With the right skilling investments, the prize is there for the taking.

It’s about developing a blend of skills

To many, the response to the skills crisis is simple: train more engineers; raise the number of arts graduates. But creating larger cohorts with certain skills is not the answer. Two things stand out in our analysis:

Creativity, socio-emotional intelligence, and complex reasoning are the skills that are rising in importance across every work role. These skills are not taught in today’s learning systems. They are acquired through practice, and experience and often over long-time periods. The blend of skills required by each worker is becoming more complex. There needs to be a greater emphasis on broadening the variety of skills within each worker.

What we need to do

  • Speed up Experiential Learning:
    From design thinking in the board room to simulation training tools for technical roles; from on-the-job training initiatives to apprenticeships. Apply new technologies like virtual reality and AI to make learning more immersive, engaging, and personalized.
  • Shift focus from Institutions to Individuals:
    Incentivize each individual to develop a broader blend of skills, rather than only targeting the output of institutions in terms of graduates or certifications.
  • Empower Vulnerable Learners:
    Support older workers, those in lower-skill roles or in smaller businesses, who can be more vulnerable to work dislocation and have less access to training. Offer more guidance to follow appropriate training and career pathways. Provide modular learning to suit their life commitments. Provide new funding models, such as grants, to encourage personal lifelong learning plans.

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