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    You are at:Home»All Africa – Construction & Infrastructure»Building AI infrastructure is the “largest in human history”
    All Africa – Construction & Infrastructure

    Building AI infrastructure is the “largest in human history”

    Xsum NewsBy Xsum NewsFebruary 1, 2026No Comments3 Mins Read4 Views
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    Switzerland – Ekbari Communication

    DAVOS, Switzerland – Jensen Huang, CEO of NVIDIA, the world’s leading chip design company, announced at the annual World Economic Forum (WEF) in Davos that the ongoing construction of artificial intelligence (AI) infrastructure is “the largest infrastructure build in human history.” Mr. Huang emphasized that this monumental undertaking is not only a technological leap forward, but also a deep economic driver poised to create a huge number of jobs across various sectors of the global economy.

    AI as a multi-layer economic engine

    In his speech, Huang introduced AI not as a single technology, but as a sophisticated “five-layer cake” that includes key components from energy production and advanced microchips to robust computing infrastructure, expansive cloud data centers, sophisticated AI models, and ultimately the application layer. He said each of these tiers requires development, operation and ongoing maintenance, which creates a wide range of employment opportunities. These jobs span a variety of sectors, including energy, traditional construction, advanced manufacturing, cloud operations, and cutting-edge application development. The application layer in particular is expected to see the greatest economic benefits as AI is integrated into critical industries such as financial services, healthcare, and manufacturing. “It is this top layer that ultimately becomes the source of economic benefits,” Huang said, highlighting the transformative potential of AI in real-world applications.

    Job creation and economic transformation

    Rapid advances in AI are already creating significant demand for skilled labor, from experts in power generation and chip manufacturing to data center construction and complex cloud management. Hwang firmly refuted concerns that AI could lead to widespread unemployment. Rather, he argued that AI technology is expanding demand in existing fields, citing radiology as an example of how AI can enhance capabilities. Additionally, AI has proven to be helpful in reducing administrative burden for sectors facing labor shortages. He noted that there is a shortage of about 5 million nurses in the United States, and one reason for this is that nearly half of nurses’ time is spent keeping medical records. AI can now take on this responsibility, freeing up healthcare professionals to focus on direct patient care.

    AI as critical national infrastructure

    “AI is infrastructure,” Huang declared, drawing parallels between AI and basic utilities like electricity and roads. He urged countries to consider AI as an integral part of their national infrastructure. “Learning how to leverage AI—how to guide it, manage it, control its operations, and evaluate it—is absolutely critical,” advised Huang, likening these competencies to leadership and people management skills. For developing countries, AI presents an unprecedented opportunity to bridge long-standing technology gaps. He also encouraged European countries to integrate their industrial strengths with AI and unleash the full potential of physical AI and robotics.

    Investment and future prospects

    BlackRock CEO Lawrence D. Fink, who participated in the discussion, echoed Huang’s optimistic outlook and suggested that the current investment climate shows the world is far from an “AI bubble.” In response to a question about the adequacy of AI investment, Huang acknowledged the need for significant capital. He highlighted that record venture funding will be invested in AI globally in 2025, exceeding $100 billion, with the majority going to AI-native startups across healthcare, robotics, manufacturing, and financial services. “These investments are directly creating jobs,” Huang said, noting the demand for plumbers, electricians, contractors, steel workers, network technicians and teams responsible for installing and operating advanced equipment. These are areas “for the first time that models are good enough to build things on top of,” he emphasized.

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