The Future of Workplace Learning
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The promise — and threat — of AI is real. But the impact on jobs has not yet arrived in most organizations. As recently as 2017, headlines such as “Bosses Believe Your Work Skills Will Soon Be Useless” (from the The Washington Post) were common. Oxford University researchers argued in 2013 that 47% of U.S. jobs were at risk of loss to automation. MIT launched its institute-wide task force on the future of work in 2018. Leaders around the world began to consider how their organizations would be different when thousands of their employees’ jobs are automated away.
Fast-forward a few years, and the story is different. As with many technologies, reality did not keep up with the hype — at least not right away. The analysts, managers, and industry gurus forgot the first law of digital innovation: Technology changes quickly, but organizations change much more slowly. Many people are working with smart machines in their daily work, but few have lost their jobs to them.
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Job change, however, is more likely. A 2021 McKinsey study estimated that 6% of workers — particularly those in low-wage roles — may need to find new jobs because of automation and the pandemic. A 2018 Deloitte survey found that 82% of AI adopters expected moderate or substantial job changes for their employees in three years.
The experience of the past decade shows the difficulty of predicting the timing and effect of technology on workers and skills. In November 2020, the MIT Task Force on the Work of the Future’s final report stated, “In the two-and-a-half years since the task force set to work, autonomous vehicles, robotics, and AI have advanced remarkably. But the world has not been turned on its head by automation, nor has the labor market.” The delay of the day when AI and robots eat jobs has toned down the level of hype in the media and reduced the level of concern for many managers and workers. But some leaders are still considering how to prepare their companies, and their workers, for changes that will come as organizational data feeds and machine learning algorithms mature.
Many people are working with smart machines in their daily work, but few have lost their jobs to them.