AI is described as “fundamentally transforming the global job market,” reshaping skills, professions, and wages while generating sharply different predictions, from “mass worker displacement” to a “productivity revival.” Historical comparisons show that previous general-purpose technologies took decades to spread, but AI is expected to diffuse faster, possibly fueling an investment boom or even a “bubble,” with uncertainty about how quickly labor markets will adjust. Instead of focusing only on direct job replacement, the text emphasizes the need to build resilience that can handle simultaneous technological, demographic, and geoeconomic shifts, such as weakening trade and foreign direct investment in labor‑intensive sectors and new job “booms” in defense, chipmaking, critical minerals, and agrifood across various countries. Demographic trends create divergent pressures: aging societies with strict immigration, like Japan, tend to accelerate automation, while developing economies face the entry of around “1.2 billion young people” into the workforce, which heightens demand for jobs but can also be undercut by cheap labor‑saving technologies, as past experiences in China, Bangladesh, East Asia, and India illustrate.
Lifelong learning appears as a central “win‑win” response for both rich and poor countries, not necessarily requiring more public spending but smarter use of funds through modernized job centers, real‑time labor‑market data, and close collaboration between universities, business, and government to provide AI, digital, human‑centric, business, green, and vocational skills for “the economy of tomorrow,” with Nordic countries, Singapore’s SkillsFuture, and Brazil’s skills accelerator cited as leading examples. AI‑intensive sectors like healthcare, where research on radiology tools across U.S. systems shows that technical deployment alone does not guarantee “meaningful clinical impact” without investment in AI literacy, training, workflow redesign, and clinician readiness. For many developing economies, a promising strategy involves treating entrepreneurship policy as a kind of industrial policy by combining abundant youth talent and relatively cheap technology to support freelancing, small firms, and digital enterprises in areas like software, digital marketing, consulting, and creative services, as seen in initiatives such as Nigeria’s National Talent Export Programme. Overall, concentrating narrowly on any single technology, including AI, risks leading to misguided decisions about jobs and that effective responses must integrate technology, demographics, and geoeconomics into coherent talent and employment strategies.
Reference
Zahidi, S. (2026, January 23). The real economics of AI and jobs. TIME. https://time.com/7357476/economics-of-ai-and-jobs/