International Business & Economy Singapore workers are the world's fastest in acquiring AI skills — LinkedIn...

Singapore workers are the world’s fastest in acquiring AI skills — LinkedIn report

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LinkedIn researchers also identified a list of over 500 skills likely to be affected by generative artificial intelligence (GAI) technologies, including these skills most frequently featured in the profiles of LinkedIn members

SINGAPORE: Singapore workers are the world’s fastest in acquiring artificial intelligence skills, according to LinkedIn’s Future of Work report. The report covered 25 countries, including the US, UK, Australia, Israel, Switzerland, France, Germany, Netherlands, Denmark, and Sweden.

The report says: “As of June 2023, Singapore has the highest diffusion rate over time (20x); in other words, the share of members who have added AI skills to their profiles is 20x as compared to January 2016. Finland (16x), Ireland (15x), India (14x), and Canada (13x) round out the top five countries with the highest rates of AI skills diffusion. LinkedIn’s AI Skills 20 Index shows that the share of AI-skilled members in June 2023 is 9x as compared to 2016.”

The year 2016 was a landmark for LinkedIn and artificial intelligence.

  • Microsoft acquired LinkedIn in 2016;
  • Artificial intelligence programs developed by Microsoft and Alibaba in 2016 achieved better average performance on a Stanford University reading and comprehension test than human beings.
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The launch of ChatGPT in November 2022 has hastened the pace of the acquisition of AI skills.

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The LinkedIn report says that “the pace at which LinkedIn members added AI skills to their profiles nearly doubled since the launch of ChatGPT, rising from 7.7% (May–November 2022) to 13% (November 2022–June 2023).”

The market demand for AI skills is increasing. The report says:

“Job postings referencing new AI technologies also are climbing rapidly: The share of global English-language job postings mentioning GPT or ChatGPT increased 21x since November 2022. Professionals and businesses are starting to embrace AI-assisted technologies, such as ChatGPT, in their daily work.”

But what exactly are AI skills?

The report explains:

“There are 38,000 skills in LinkedIn’s skills taxonomy, of which 121 are considered AI skills, including machine learning, natural language, and deep learning.”

However, the need for AI skills is not limited to the technology sector. AI is needed in other sectors, too, from financial services to manufacturing. And only a tiny fraction of the workforce currently possesses these skills.

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The report says:

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“As might be expected, in the US, Technology, Information, and Media have the largest share of AI-skilled members (2.2%); while small, this is still well above other industries such as such as Education (1.2%), Professional Services (0.9%), Financial Services (0.9%), and Manufacturing (0.8%). However, other industries are quickly catching up. When we look at the speed at which members are adding AI skills to their profiles, we see that professionals in Financial Services (30x), Retail (29x), and Wholesale (24x) are pivoting toward AI faster than in Technology, Information, and Media (11x).”

Employers will need to “focus on upskilling and reskilling professionals to boost AI literacy,” says the LinkedIn report. And the need to boost “AI literacy” will have another consequence.

The report says:

“Competition is intensifying to hire talent to fill specialized AI roles. Since many of these roles are brand new and no existing degree completely satisfies the role, filling them will require an increased emphasis on hiring for skills.”

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LinkedIn researchers identified a list of over 500 skills likely to be affected by generative artificial intelligence (GAI) technologies, including these skills most frequently featured in the profiles of LinkedIn members:

  • Business and industry: Financial reporting, email marketing, data analysis
  • Communication and media: Writing, editing, translation, content creation
  • Engineering: Software development tools, programming languages, data science
  • People: Time management tools.
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