CNA
December 10, 2023
SINGAPORE: In the race to harness the power of artificial intelligence (AI), Singapore aims to get ahead by more than tripling its AI workforce to 15,000 in the next three to five years.
This goal is achievable, according to industry observers, who see the figure as a starting point and as a critical mass needed for innovation.
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Mr Adrian Goh, co-founder of tech talent platform Nodeflair, said government support to foster tech trends and welcome innovation - as seen in cryptocurrency-friendly policies - has helped make Singapore attractive.
The country's strong English proficiency also attracts global companies like FAANG - Meta (formerly Facebook), Apple, Amazon, Netflix and Google - and Nvidia, while the high quality of life appeals to overseas AI talent.
Compared to the United States, where tech workers face challenges securing visas, Singapore has a streamlined employment pass system, Mr Goh added.
On the other hand, compared to Singapore, other countries in the region offer "cost-efficient growth options" with their emerging talent pools, he said.
Singapore's software engineers have the highest median salaries among seven Asian economies, according to a recent Nodeflair report. The median salary for a lead software engineer was about S$6,600, versus S$2,400 in Malaysia and S$2,100 in Vietnam, which had the next highest salaries.
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Nodeflair's Mr Goh said that while software engineers and data analysts are already well-suited for transitioning into AI, domain-specific professionals trained in data science and machine learning also have an important role to play.
This is because understanding the nuances of a domain is valuable when working on AI applications.
While more training is required for such workers to make the career switch to AI, they are "much more valuable talent", he said.
The level of AI proficiency they would need to attain depends on the role, ranging from a developer creating large language models, to a developer working on a product that incorporates an application programming interface (API).
"To illustrate, it's like comparing building a car engine from scratch (the first scenario) to simply fitting a car engine into the rest of the car (the second scenario)," said Mr Goh.
He stressed that even someone with software development experience will need continual learning to make sure their skills stay relevant, given the fast-evolving nature of the AI field.
And for those employed by tech companies, basic AI proficiency is increasingly expected as a core technical competency due to the pervasiveness of AI in business operations, said Mr Goh.
This is reflected in offerings at universities, where AI is being incorporated as a core subject for computer science students.
