The worldwide boom in generative artificial intelligence will usher in an age of accelerated productivity and greater prosperity for some — and profound disruption for others, primarily knowledge workers, according to a new report by consultants McKinsey & Co.
Whole swaths of business activity, from sales and marketing to customer operations, are set to become more embedded in software — with potential economic benefits of as much as $4.4 trillion, about 4.4% of the world economy’s output — according to the study by McKinsey’s research arm.
Generative AI will give humans a new “superpower”, and the economy a much-needed productivity injection, said Lareina Yee, a senior partner at the firm and chair of McKinsey Technology, in the report.
The research examined 63 use cases for generative AI, the type of tools that can generate content such as text or images based on a prompt, across some 850 occupations. Depending on how the technology is adopted and implemented, productivity increases could range between 0.1% and 0.6% over the next 20 years, it found.
“Business leaders need to understand which activities can be changed, and how they want to rethink that,” said Yee. “That is a leadership choice, and it’s also execution.”
The transformation will pile pressure on the labor force, especially for higher-wage knowledge workers whose activities “were previously considered to be relatively immune from automation,” the report said.
A few years ago, McKinsey had estimated that about half of worker hours worldwide were spent on tasks that could be automated. Now it’s raising the figure to as high as 60-70%. Employees could find that their time is reallocated — or that their jobs disappear. “Workers will need support in learning new skills,” the report said. “Some will change occupations.”
Happening Fast
About 75% of the potential value from applied generative AI will come in four business functions: customer operations, marketing and sales, software engineering, and research and development.
Banks alone could generate an additional $200-$340 billion from increased productivity, the report found, as the new technology improves customer satisfaction, helps decision-making and mitigates fraud through better monitoring. That would equate to a jump in operating profits of somewhere between 9% and 15%.
Read More: Banks Warned Against Relying on Error-Prone, Alienating Chatbots
In product R&D, the technology could deliver a boost to productivity of 10% to 15%, McKinsey said. It cited the example of life sciences and chemical industries, where AI can generate potential molecules more quickly, accelerating the process of developing new drugs and materials. That could add as much as 25% to profits for pharmaceutical companies and medical product firms.
Read More: AI Drug Discovery Is a $50 Billion Opportunity for Big Pharma
And it’s all developing fast. The firm’s earlier research suggested that 2027 would be the first year when AI technology would be able to match the typical human’s performance in tasks that involve “natural-language understanding.” Now, McKinsey reckons it will happen this year.
Automation adoption will be faster in developed economies, where higher wages will make it feasible sooner, than poorer ones — and will impact white-collar work much more than physical tasks.
In that respect, it may be the opposite of major technology upgrades of the past, which often came at the expense of occupations where workers had fewer educational qualifications and got paid less. Many were performing physical tasks — like the British textile workers who smashed up new cost-saving weaving machines, a movement that became known as the Luddites.
By contrast, the new shift “will challenge the attainment of multiyear degree credentials,” McKinsey said.
McKinsey’s projections on workforce composition are consistent with a National Bureau of Economic Research working paper published this month by academics at Columbia Business School, the University of Maryland, University of California at Berkeley and AI for Good.
That study also predicted a significant reorganization of labor. “AI investments are associated with a flattening of the firms’ hierarchical structure, with significant increases in the share of workers at the junior level and decreases in shares of workers in middle-management and senior roles,” it found.
