Some forecasts project that advances in automation will result in the wholesale replacement of the human workforce. Encompassing the near- or medium-term timeframes, our analysis suggests another perspective: that work currently performed by humans is being augmented by machine and algorithmic labour. Responses from employers surveyed for this report can be interpreted as evidence for the increasing viability of what a number of experts have called an ‘augmentation strategy’. Namely, it has been suggested that businesses can look to utilize the automation of some job tasks to complement and enhance the human workforces’ comparative strengths and ultimately to enable and empower employees to extend to their full potential and competitive advantage. Rather than narrowly focusing on automation-based labour cost savings, an augmentation strategy takes into account the broader horizon of value-creating activities that can be accomplished by human workers, often in complement to technology, when they are freed of the need to perform routinized, repetitive tasks and better able to use their distinctively human talents.
Importantly, most automation occurs at the level of specific work tasks, not at the level of whole jobs.15 For example, according to one recent study, whereas nearly two-thirds of today’s job roles entail at least 30% of tasks that could be automated based on currently available technology, only about one-quarter of today’s job roles can be said to have more than 70% of tasks that are automatable. A similar recent analysis finds that workforce automation is likely to play out in three waves between today and the mid-2030s, increasing the share of fully automatable manual tasks in the most affected current job roles from less than 5% today to nearly 40% by the mid-2030s, and the share of automatable tasks involving social skills from less than 5% today to about 15% in the same time horizon.17 The most relevant question to businesses, governments and individuals is not to what extent automation will affect current employment numbers, but how and under what conditions the global labour market can be supported in reaching a new equilibrium in the division of labour between human workers, robots and algorithms. Workforce planning and investment decisions taken today will play a crucial role in shaping this process.
Waves of automation have reshaped the global economy throughout history. Since the first and second industrial revolutions, organizations have bundled specific work tasks into discrete job roles, giving rise to distinct occupational profiles and optimizing the process of economic value creation based on the most efficient division of labour between humans and machines technologically available at the time. As technological change and progress have increased workforce productivity by ‘re-bundling’ work tasks into new kinds of jobs, so they have seen the decline of obsolete job profiles and the dynamic rise of wholly new ones, historically leaving the balance of net job and economic value creation firmly on the positive side.
While the Fourth Industrial Revolution’s wave of technological advancement will reduce the number of workers required to perform certain work tasks, responses by the employers surveyed for this report indicate that it will create increased demand for the performance of others, leading to new job creation. The rise of workplace automation in its many forms has the potential to vastly improve productivity and augment the work of human employees. Automation technology can help remove the burden of repetitive administrative work and enable employees to focus on solving more complex issues while reducing the risk of error, allowing them to focus on value-added tasks. Examples of now well-established and almost unremarkable automation-based augmentation technology that hardly existed 25 years ago range from computer-aided design and modelling software used by architects, engineers and designers, to robotic medical tools used by doctors and surgeons, through to search engine technology that allows researchers to find more relevant information. In theory, these technologies take away tasks from workers, but in practice, their overall effect is to vastly amplify and augment their abilities.
The estimates of companies surveyed for this report provide a nuanced view of how human-machine collaboration might evolve in the time horizon up to 2022. In today’s enterprise, machines and algorithms most often complement human skills in information and data processing. They also support the performance of complex and technical tasks, as well as supplementing more physical and manual work activities. However, some work tasks have thus far remained overwhelmingly human: Communicating and interacting; Coordinating, developing, managing and advising; as well as Reasoning and decision-making. Notably, in terms of total working hours, in the aggregate, no work task was yet estimated to be predominantly performed by a machine or an algorithm.
By 2022, this picture is projected to change somewhat. Employers surveyed for this report expect a deepening across the board of these existing trends, with machines and algorithms on average increased their contribution to specific tasks by 57%. Relative to their starting point today, the expansion of machines’ share of work task performance is particularly marked in Reasoning and decision-making; Administering; and Looking for and receiving job-related information. The majority of an organization’s information and data processing and information search and transmission tasks will be performed by automation technology
Based on one recent estimate, the next wave of labour-augmenting automation technology could lead to an average labour productivity increase across sectors of about 30% compared to 2015, with some significant variation by industry.25 For employers, optimally integrating humans and automation technology will require an analytical ability to deconstruct the work performed in their organizations today into discrete elements—that is, seeing the work tasks of today’s job roles as independent and fungible components—and then reconfiguring these components to reveal human-machine collaboration opportunities that are more efficient, effective and impactful. Among other things, success in this domain will require a strategic repositioning of the corporate human resource function and expanded organizational capabilities in data analysis and workforce analytics.
For workers, improved productivity may allow them to re-focus their work on high-value activities that play to the distinctive strengths of being human. However, to unlock this positive vision, workers will need to have the appropriate skills that will enable them to thrive in the workplace of the future. And as discussed in detail in the next section, even for those who currently have these skills, the pace at which tasks are being augmented and skills are changing continues to accelerate.
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