AI Could Double Value of Digital Economy by 2025: Huawei
AI Could Double Value of Digital Economy by 2025: Huawei
The research suggests that governments worldwide need to re-think education for a future workplace redefined by AI and start building a healthy, collaborative, and open AI ecosystem to attract and retain competitive AI talent.

Artificial Intelligence (AI) could almost double the value of the global digital economy to $23 trillion by 2025 from $12.9 trillion in 2017, said a Huawei study on Tuesday. However, a scarcity of AI talent worldwide threatens this growth, showed the study, Global Connectivity Index (GCI) 2018, which is now in its fifth year. The digital economy accounted for 17.1 percent of global GDP in 2017, it added. The research suggests that governments worldwide need to re-think education for a future workplace redefined by AI and start building a healthy, collaborative, and open AI ecosystem to attract and retain competitive AI talent.

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"We are now witnessing a paradigm shift initiated by AI," said Kevin Zhang, President of Huawei Corporate Marketing. "According to the GCI study, advanced economies that saw growth from ICT development plateau are using Intelligent Connectivity to open new opportunities, while some developing economies are also finding ways to tap the new technology to speed up their own strategic growth plans," Zhang added.

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The study found that industries are embedding AI in key enabling technologies -- broadband, data centres, Cloud, big data and IoT (Internet of Things) -- to turn connectivity into Intelligent Connectivity, unleashing innovation to propel a new wave of economic growth. In 2018, the GCI broadened its research scope from 50 to 79 nations. For the first time, every nation in the Index saw GCI scores improve.

From 64 in 2017, India improved its ranking to 63 in the 2018 GCI Index which was topped by the US. The GCI 2018 also discovered that to effectively deploy AI on a large scale, countries need three equally important components in place -- computing power, labelled data and algorithms.

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