![]() Artificial intelligence is also making major strides that are increasing the potential for automating work activities in many industries: in one recent test, for example, computers were able to read lips far more accurately than professionals. A new generation of robots that are more flexible and versatile, and cost far less, than those used in many manufacturing environments today can be “trained” by frontline staff to perform tasks previously thought to be too difficult for machines-tasks such as picking and packing irregularly spaced objects, and resolving wiring conflicts in large-scale projects in, for example, the aerospace industry. Moreover, it is notable that recent technological advances have overcome many of the traditional limitations of robotics and automation. (see sidebar, “Understanding automation potential”). In some cases, that level of performance has been demonstrated through commercially available products, in others through research projects. We define “currently demonstrated technologies” as those that have already exhibited the level of performance and reliability needed to automate one or more of 18 capabilities involved in carrying out work activities. We emphasize that the potential for automation described above is created by adapting and integrating currently demonstrated technologies 3 3. For more, see “ Harnessing automation for a future that works,” McKinsey Global Institute, January 2017. As McKinsey research has shown, manufacturing is second, among industry sectors, only to accommodation and food services in terms of automation potential (Exhibit 1). These figures suggest that, even though manufacturing is one of the most highly automated industries globally, there is still significant automation potential within the four walls of manufacturing sites, as well as in related functional areas such as supply chain and procurement. These 478 billion working hours represent the labor equivalent of 236 million out of 372 million full-time employees-$2.7 trillion out of $5.1 trillion of labor-that could be eliminated or repurposed, assuming that demonstrated technologies are adapted for use in individual cases and then adopted. This includes activities that currently have some elements of automation (for example, sending email). The baseline we used to determine which manufacturing activities are “automatable” is “current activities” as defined by the US Bureau of Labor Statistics. Working hours (64 percent) spent on manufacturing-related activities globally were automatable with currently demonstrated technology. ![]() Our data and analysis show that as of 2015, 478 billion of the 749 billion ![]() ![]() ![]() To understand the scope of possible automation in the manufacturing sector as a whole, we conducted a study of manufacturing work in 46 countries in both the developed and developing worlds, covering about 80 percent of the global workforce. How manufacturing work-and manufacturing workforces-could change Industry executives-those whose companies have already embraced automation, those who are just getting started, and those who have not yet begun fully reckoning with the implications of this new automation age-need to consider the following three fundamental perspectives: what automation is making possible with current technology and is likely to make possible as the technology continues to evolve what factors besides technical feasibility to consider when making decisions about automation and how to begin thinking about where-and how much-to automate in order to best capture value from automation over the long term. Today, we are on the cusp of a new automation era: rapid advances in robotics, artificial intelligence, and machine learning are enabling machines to match or outperform humans in a range of work activities, including ones requiring cognitive capabilities. Over the past two decades, automation in manufacturing has been transforming factory floors, the nature of manufacturing employment, and the economics of many manufacturing sectors. ![]()
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