Where and how will generative AI have its greatest business impact? There is no shortage of speculation and high hopes that AI will shorten innovation cycles, spur new ideas, write and check code, and relieve workers and executives alike of the drudgeries of manual tasks. It could go even deeper, adding the equivalent of $2.6 trillion to $4.4 trillion annually.
That’s the word from a recent report out of McKinsey, in which the co-authors observe that “all of us are at the beginning of a journey to understand generative AI’s power, reach, and capabilities.”
Generative AI, the McKinsey team notes, is very good at performing routine tasks, such as reorganizing and classifying data. That’s a logical step in automation. But generative AI opens new doors when it delivers creative output. This is new stuff, and “as a result, a broader set of stakeholders are grappling with generative AI’s impact on business and society but without much context to help them make sense of it.”
The co-authors predict over the next several years, AI “will take us on a roller-coaster ride featuring fast-paced innovation and technological breakthroughs that force us to recalibrate our understanding of AI’s impact on our work and our lives,” the report states. Generative AI will transform roles and boost performance — especially across functions such as sales and marketing, customer operations, and software development.
The transformation of work is where and how generative AI will deliver a lot of value. It will “change the anatomy of work, augmenting the capabilities of individual workers by automating some of their individual activities,” the McKinsey team says. “Current generative AI and other technologies have the potential to automate work activities that absorb 60 to 70 percent of employees’ time today.” This will likely occur over a period of two decades, they add.
This is a step up from McKinsey’s previous estimate that technology has the potential to automate half of work activities. “The acceleration in the potential for technical automation is largely due to generative AI’s increased ability to understand natural language,” which will help boost knowledge work.
Of course, as the McKinsey authors point out, future realities don’t always cooperate with futuristic technology predictions — and this is definitely the case with AI. “Technology adoption at scale does not occur overnight,” the co-authors caution. Even when 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.”
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