The Workforce in 2030

We are living through a fundamental transformation in the way we work. Automation and 'thinking machines' are replacing human tasks, changing the skills that organisations are looking for in their people. But what will the future look like?


Our 'Workforce of the future' study looks at four possible Worlds of Work for 2030 and the views of 10,000 people. Did you know that:

  • 37% are worried about automation putting jobs at risk - up from 33% in 2014.
  • 74% are ready to learn new skills or re-train to remain employable in the future.
  • 60% think 'few people will have stable, long-term employment in the future.
  • 73% think technology can never replace the human mind.

Over this week we will introduce you to the Blue, Red, Yellow and Green worlds, to kick start your thinking. Let's start with the Blue world.

In the Blue World, corporate is king

In the blue world, big company capitalism rules as organisations continue to grow bigger.

  • Organisations see their size and influence as the best way to protect their profit margins against intense competition from their peers and aggressive new market entrants.
  • Corporations grow to such a scale, and exert such influence, that some become more powerful and larger than national economies.
  • It's a world where individual preferences take precedence over social responsibility.


In the Blue World, it’s a world of extreme talent

In this world, a corporate career divides the haves and have-nots.

  • Extensive use of automation and AI enhance productivity and quality, but humans are still in demand.
  • Exceptional people are in high demand, so employers secure a core group of pivotal high-performers by offering excellent rewards. But workforces are lean and organisations bring in flexible talent and skills as and when they're needed.
  • Human effort is maximised through the use of physical and medical enhancements. And sensors and data analytics continually measure, analyse and optimise performance at every step.
  • Rewards in this world are high, but the price workers pay is their data. Data is used to predict performance and anticipate people risk.

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