Over the past two and a half centuries, the world has experienced five technological revolutions, according to economic historian Carlota Perez. Each revolution occurs about every half century, brings together multiple interrelated technologies and produces profound socio-economic shifts. In the early stages of these revolutions, notes Perez, people often fear that skills, jobs and industries will be upended—and for good reason.
Given this long historical pattern, will generative AI, with capabilities so different from any of its predecessor technologies, follow the same trajectory? Will its benefits flow mostly to the economically privileged who already have full access to and familiarity with digital technologies?
As generative AI begins to move into the mainstream in 2024, I believe this technology could break that trend and become an equalizer for society broadly.
Gen AI: a different kind of tech disruption
Here are a few reasons why. To begin, generative AI has qualities that depart from prior technology waves, such as its outsized productivity power. In partnership with Oxford Economics, Cognizant analyzed the economic impact of generative AI in the US and forecasts this technology could add as much as $1 trillion to US GDP and boost worker productivity by 10% and total factor productivity by 3.5% by 2032. Increasing the economic pie is broadly viewed as a key route to prosperity for all.
Generative AI is also simple to use. In the past, people needed to know a programming language to efficiently use AI. No longer. Knowledge of a natural language is now sufficient to use some of the most powerful AI tools available. As AI expert Andrej Karpathy observed, “the hottest new programming language is English.” Therefore, solving problems using AI has become much easier and more broadly accessible, aided also by the ability to use some forms of generative AI for free, such as Microsoft Bing and Google Bard.
Productivity gains of gen AI
No question, as generative AI is adopted increasingly by businesses, workers will face a major adjustment. Last year, most workplace tasks could not be assisted or automated by generative AI. But by 2032, Cognizant’s research predicts that generative AI could be capable of both influencing a greater share of tasks and automating them to a greater degree.
Our research shows that over the next 10 years, 90% of jobs could experience some degree of disruption. Everyone from entry-level number crunchers to heads of business units and even C-suite executives will see their jobs evolve over the next decade.
But in contrast with prior computerization waves, the productivity gains associated with generative AI seem to go disproportionately to less experienced, lower skilled workers. In a recent National Bureau of Economic Research working paper titled “Generative AI at Work,” the authors (Erik Brynjolfsson, Danielle Li, and Lindsey Raymond) conclude that generative AI benefits the less skilled because “gen AI systems work by capturing and disseminating the patterns of behavior that characterize the most productive [customer support] agents, including knowledge that has eluded automation from earlier waves of computerization.” Generative AI seems to speed individual learning by enabling novice workers to progress more rapidly along the experience curve compared with those who don’t use this capability.
Likewise, a working paper from MIT titled “Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence” suggests that “inequality between workers decreases as ChatGPT compresses the productivity distribution by benefiting low-ability workers more.”
A balance wheel
If, as this early research suggests, generative AI may asymmetrically benefit the less skilled and less productive, what societal changes could result? We can recall educational reformer Horace Mann’s observation that “education, beyond all other devices of human origin, is the great equalizer of the conditions of men, the balance wheel of the social machinery.” Could generative AI become a new balance wheel of society?
I believe so, especially if we can demystify how generative AI works, be transparent about how and where it’s deployed, commit to mitigating any detrimental effects of the technology and, above all, roll out a new generation of reskilling programs on a vast scale.
How might this happen? Rather than an optional add-on to an employee’s work life, reskilling will need to become an essential part of everyone’s workday. Businesses could partner with higher education institutions to continually revamp curricula in select skill areas. Organizations could collaborate with policy makers, government officials and regulators to create shared “academy” systems that would not only teach generative AI skills but also establish new job tracks for people in roles where many tasks are likely to be fully automated by generative AI.
Keep in mind that generative AI can be deployed flexibly to accentuate people’s existing strengths while deemphasizing their weaknesses, thereby enabling an array of cognitive capabilities to be used in a wider range of roles.
Building greater trust in AI will also be crucial to ensuring its beneficial effects prevail. That’s why Cognizant recently surveyed 1,000 US consumers to discern how the level of trust and understanding of generative AI affects how they perceive this technology. While split between enthusiasm and concern, consumers are overwhelmingly positive that generative AI will make other technologies easier to use. More than half said generative AI will increase access to innovation and benefit education. And more than half also agreed that getting high-paying jobs will be easier because people can use the technology to supplement and boost their skills. The majority, however, said the widespread use of generative AI could result in greater competition for jobs—perhaps a sign of generative AI’s ability to democratize skills.
Recognizing generative AI’s potential to greatly expand our knowledge, skills and productivity, it seems this technology could, over time, bring many more people into more highly compensated work. Aided by a generative AI assistant, we can imagine a nurse taking over more tasks from doctors, while doctors have more time to focus on complex medical cases and intensive patient interaction, enhancing the overall quality of care.
The end of the digital divide?
To be sure, we are early in generative AI’s evolution. Still, the optimist in me believes this technology could significantly boost social mobility by bridging the longstanding digital divide and providing more people with access to well-paying jobs, while shrinking the wage premium granted to the most credentialed.
As a corollary, generative AI may also depress the compensation of some jobs held by the most educated by automating the knowledge work that used to be their exclusive domain. Therefore, by raising the socio-economic floor while lowering the ceiling, perhaps generative AI may, over time, become the new balance wheel of society.
For more insights, read our report “New World, New Work,” visit our Generative AI webpage or contact us.