The ‘Automation’ Disruption and Davos: Why Executives Should Worry about How Employees Learn

The global workforce faces an “epochal transition” as digitization, automation, and artificial intelligence (AI) make further inroads – a message that took center stage at the World Economic Forum at Davos, where the need to retrain workers reverberated among the business and political elite. As Fortune observed, technology will “obliterate work as we know it,” which changes the conversation to “how to encourage the necessary ‘re-skilling’ in response.”

With a McKinsey study estimating that as much as 14% of the global workforce will be impacted, it’s clear that simply moving these workers into other roles will not suffice. The key is effective retraining, to ensure employees needing new and higher-level skills are truly equipped to compete and contribute as we enter the Fourth Industrial Revolution.

Now, in response to the urgent need to retool a significant portion of the global workforce, employers must deploy an advanced corporate learning strategy centered around an adaptive approach. Adaptive learning brings together computer science and cognitive research to deliver a personalized, online, while still a one-on-one tutor-like experience.

It is a common misconception that we can just ignore knowledge in the future because we all have a smartphone in our pocket. While what we learn most certainly will change, there is still a significant need to accomplish automaticity — i.e., the knowledge and skills that must be readily available to efficiently practice and perform 21st skills of communication, collaboration, creativity, and critical thinking. Adaptive learning is shown to be effective to secure the necessary knowledge and cognitive skills in a more efficient and reliable way to equip humans for the AI-enabled economy.

Greater Accountability for Corporate Training

The stakes for learning and training are higher than ever as the roles of humans and machines blur and merge. While early educational technology (EdTech) has made promises, such as computer-based learning that can lower training costs by putting material online, few have realized that’s not how humans learn. Online learning with static content disengages learners and limits progress.

Global spending on training and corporate learning amount to an estimated $360 billion, of which $162 billion is spent in North America, often with questionable results. Millions of dollars have been wasted on ineffective training, such as standardized learning that is not adapted to the individual’s level or special needs for developing new skills. Such learning produces little or no impact, and up to 70 percent of the information is forgotten by the next day unless the learner makes sense of what is attempted to be learned.

Within the next five years, I believe, companies increasingly will demand greater accountability for corporate learning and training as they endeavor to determine whether talent is being developed in the most effective and efficient way. Already, we’re seeing large banks, insurance companies, consulting firms, and other large firms looking for a measurable return on their investment in corporate learning. Adaptive learning, which automatically tracks what learners have mastered, where they needed reinforcement, and what they have learned, provides the greater accountability in corporate learning and training that some major employers are beginning to demand.

At the same time, in the age of automation, adaptive learning must continue to evolve. Technology is advancing rapidly, as evidenced by huge breakthroughs that demonstrate the increasing pace at which computers can learn. To provide context, we can compare the scope and impact of these new technologies to the invention of the steam engine, which ushered in the modern industrial age. Unlike previous workforce disruptions, such as a gradual shift from agricultural work to manufacturing as seen in North America in the early 20th century and more recently in China, McKinsey noted, “The task [now] confronting every economy, particularly advanced economies, will likely be to retrain and redeploy tens of millions of midcareer, middle-age workers.”

Breakthrough, intelligent technologies in teaching and training people has the promise to deliver more effectively and efficiently and with better quality results. In addition, practical applications of adaptive learning reveal an important factor: Success is enhanced in a blended environment. For training such as onboarding, using adaptive learning can vastly improve the student-teacher ratio. A teacher can work with learners in small groups to reinforce skills and their application, while adaptive learning approximates a one-on-one experience for certain kinds of learning. Adaptive learning solutions become highly efficient and produce quality results by homing in on what each learner needs to master and through shaping individual learning paths to proficiency. Probing prior knowledge allows each student to skip what they already know, while focusing on filling knowledge gaps, correcting faulty assumptions, and building competence.

For such blended solutions to be more widely adopted, companies will have to look beyond price, alone: Standardized and static online content is certainly cheaper. But when the ineffectiveness of basic online learning is factored in, the wasted millions show that cheaper is not better. What’s needed is learning technology to make employees more competent and confident in what they know: improving performance, enhancing safety, elevating customer satisfaction, and reducing errors and accidents. This is the promise and potential of adaptive learning at a time of urgent need to improve the retraining and retooling of workers in the age of automation.