【英文】麦肯锡报告：生成式人工智能的经济潜力（68页）

Technology has been changing the anatomy of work for decades. Over the years, machines  have given human workers various “superpowers”; for instance, industrial-age machines  enabled workers to accomplish physical tasks beyond the capabilities of their own bodies.  More recently, computers have enabled knowledge workers to perform calculations that  would have taken years to do manually.  These examples illustrate how technology can augment work through the automation of  individual activities that workers would have otherwise had to do themselves. At a conceptual  level, the application of generative AI may follow the same pattern in the modern workplace,  although as we show later in this chapter, the types of activities that generative AI could  afect, and the types of occupations with activities that could change, will likely be diferent as  a result of this technology than for older technologies.

Technology adoption at scale does not occur overnight. The potential of technological  capabilities in a lab does not necessarily mean they can be immediately integrated into a  solution that automates a specifc work activity—developing such solutions takes time. Even  when such a solution is developed, it might not be economically feasible to use if its costs  exceed those of human labor. Additionally, even if economic incentives for deployment exist, it  takes time for adoption to spread across the global economy. Hence, our adoption scenarios,  which consider these factors together with the technical automation potential, provide a  sense of the pace and scale at which workers’ activities could shift over time.