The media today is replete with predictions of what the future of work may look like after the rise of automation and AI. Most commentaries tend to lean towards the dominant narrative of disruption, in that AI and automation will lead to the unprecedented displacement of jobs. This is widely held belief is so common that it’s now regarded as a guarantee, with most pundits disagreeing only on the year by which this result will manifest.
The reality however is far more nuanced and complex. While Mercer’s People First research shows that 62% of people believe more than half their tasks could be replaced by AI in the next five years, it also shows that 43% believe AI will make their work more efficient. Indeed, we must consider the other tectonic shifts in the world of work to make better sense of what may really be happening.
Let us go back in time to consider one of my favorite analogies for context. The arrival of ‘automated teller machines’ (ATMs) was believed to spell doom for the most common of all banking jobs in the US back in the 1970s – the teller. However, the number of bank teller jobs doubled between 1970 and 2010. While it’s indisputable that banks may have hired more tellers had it not been for the ATM, it’s also clear that machine-based efficiencies have the power to expand entire industries.[i] [ii]
So what is there to learn about the future of work from the arrival of the ATM? When considering how AI and automation will impact us in the future of work, we must first consider what work will look like in the future.
With notable exceptions such as India and Indonesia, most of the world’s workforce is aging. Improved healthcare and the resulting longevity mean people will live and work for longer, challenging global leaders and employers to fit these older workers into their organizations. But the shift to task-based job roles means that the physical constraints of doing a ‘job’ will matter less, and older workers will be able to complete some of these tasks. This represents an enormous opportunity to reimagine the future of work around a radically different workforce.
Japan is a great example of workforce adaptability, where large scale adoption of advanced robotics and machine learning has already occurred. It is often pointed out that the Japanese population is rapidly aging, and Mercer research has found that 59% of older Japanese workers’ jobs are at risk due to automation. But rather than fear this shift, Japanese CEOs are most excited [iii] about the impact of AI and automation, as it will empower them to leverage this growing elderly population in the future of work.
By comparison, countries with a wealth of young talent typically grapple with the adoption of advanced technologies, with most businesses stuck in a state of inertia. Proactive policies and institutional support for education and technology research are pivotal for these countries to ensure their human capital remains competitive amidst this technological revolution. A great example is the way the Chinese government is concentrating resources in the new Greater Bay Area to develop a hub of aspirational and highly-skilled talent. [iv]
Another shift is the current, not future, impact of advanced technologies on the way work is done and business is accomplished. A potent combination of machine learning algorithms, robotics, IoT and data analytics has meant that both the flow of information and the dissemination of knowledge are near instantaneous. With more insight on products, customers, competitors, and employees, business executives can make more informed decisions faster.
This also means that the traditional hierarchies which used to control the flow of information are being dismantled in favor of fluid teams and agile organizational structures. The increased need for people from across functional boundaries and specialties to collaborate quickly has resulted in the wide adoption of new technologies, helped in part by the proliferation of mobile, cloud and web. These technologies are specifically designed for tasks – not jobs – to be completed by a disparate and dispersed group of people, not even necessarily working for the same organization.
This unpacking of ‘jobs’ into ‘tasks’ implies that one could take an ‘assembly-line’ approach to the most complex of jobs and have these jobs done by a combination of people, both within and outside one’s own organization. Exactly how AI and automation will disrupt each may not be entirely clear for now. However it is clear that what a ‘job’ is, what constitutes this job, and how it is represented in a certain ‘job title’ are all bound to undergo a sea change.
Ultimately, the predictions may be right, as automation and AI are almost certain to impact people in the future of work. But rather than replace us, technology means that we need to embrace a ‘learning mindset’ over the traditional ‘job security’ in the workplace. This new perspective is crucial to the emerging ecosystem of talent, but it also means more flexibility in where, when and how work gets done. It is the difference in seeing advanced technologies as an opportunity rather than as a threat. And one’s position, whether as an organization or as an individual employee, will always depend on one’s degree of preparedness and mindset.