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NTUC LearningHub Survey Reveals Accelerated Business Needs In Cloud Computing And Machine Learning Outpacing Singapore Talent Supply; Skills Gap A Hindrance To Implementing These Technologies

  • Written by NTUC LearningHub
  • 89% of Singapore employers say that the pandemic has accelerated the adoption of Cloud Computing/ Machine Learning technologies in their companies
  • They cite the obstacles to adopting Cloud Computing/ Machine Learning technologies are 'the shortage of relevant in-house IT support' (64%), 'employees lack of relevant skill sets' (58%) and 'the lack of financial resources' (46%)
  • Overall, a large majority (83%) maintain that Machine Learning will remain the most in-demand Artificial Intelligence (AI) skill in 2021, while 70% say they are willing to offer a premium for talent with AI and Machine Learning skills

SINGAPORE - Media OutReach[1] - 5 February 2021 - Despite majority of Singapore employers (89%) reporting that the COVID-19 pandemic has accelerated the adoption of cloud computing and Machine Learning (ML) in their companies, obstacles abound. Singapore business leaders say that the largest hindrance to adopting cloud computing and ML technologies is the shortage of relevant in-house IT support (64%), amongst other reasons such as 'employees do not have the relevant skill sets' (58%) and 'the lack of financial resources' (46%).

NTUC LearningHub Survey Reveals Accelerated Business Needs In Cloud Computing And Machine Learning Outpacing Singapore Talent Supply; Skills Gap A Hindrance To Implementing These Technologies

These are some of the key findings from the recently launched NTUC LearningHub[2] (NTUC LHUB) Industry Insights report on cloud computing and ML in Singapore. The report is based on in-depth interviews with industry experts, such as Amazon Web Services (AWS) and NTUC LHUB, and a survey with 300 hiring managers across industries in Singapore.

While organisations are keen to adopt cloud computing and ML to improve the company's business performance (64%), obtain business insights from Big Data (59%) and perform mundane or tedious tasks (53%), a third of Singapore employers (32%) say their companies have insufficient talent to implement cloud computing and ML technologies.

To overcome this shortage, companies say they have been upskilling employees that have relevant skill sets/ roles (55%), and reskilling employees that have completely different skill sets/ roles (44%). In a further show of how organisations were willing to take steps to overcome this skills gap, three in five (61%) strongly agree or agree that they will be open to hiring individuals with relevant micro-credentials, even if these candidates has no relevant experience or education degrees.

Looking to the future, four in five employers (81%) agree or strongly agree that ML will be the most in-demand Artificial Intelligence (AI) skill in 2021. Meanwhile, seven out of 10 surveyed (70%) indicated they will be willing to offer a premium for talent with AI and ML skills. 

"The report reinforces the growing demand for a cloud-skilled workforce in Singapore, and the critical need to upskill and reskill local talent", said Tan Lee Chew, Managing Director, ASEAN, Worldwide Public Sector, AWS. "The collaboration across government, businesses, education and training institutions will be instrumental in helping Singapore employers address these skills gaps. AWS will continue to collaborate with training providers like NTUC LearningHub to make skills training accessible to help Singaporeans, from students to adult learners, to remain relevant today and prepare for the future."

NTUC LHUB's Head of ICT, Isa Nasser also adds, "While much of the talent demand encompasses technical positions such as data scientists and data engineers, businesses are also looking for staff to pick up practical ML and data science skills sets that can be applied to their existing work. That is why in today's digital age, most professionals would benefit greatly from picking up some data science skills to enable them to deploy ML applications and use cases in their organization. We highly urge workers to get started on equipping themselves with ML skills, including understanding the core concepts of data science, as well as familiarising themselves on the use of cloud or ML platforms such as Amazon SageMaker[3]."

To download the Industry Insights: Cloud Computing and ML report, visit

https://www.ntuclearninghub.com/machine-learning-cloud[4].

References

  1. ^ Media OutReach (www.media-outreach.com)
  2. ^ NTUC LearningHub (www.ntuclearninghub.com)
  3. ^ Amazon SageMaker (aws.amazon.com)
  4. ^ https://www.ntuclearninghub.com/machine-learning-cloud (www.ntuclearninghub.com)

Authors: NTUC LearningHub

Read more https://www.media-outreach.com/release.php/View/64002#Contact

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