Are Singapore workers ready for technological disruptions?
Due to the measures and policies put in place by the Singapore government, the nation’s workers are better prepared than those in other global cities for technological disruptions due to AI and automation.
Citing a survey conducted with 1,000 Singaporean workers as part of a report complied by PayPal titled “Financial Health for the Future of Work,” the online payments system firm said Singaporeans are “overwhelmingly positive” about automation. 89% of survey respondents believe that automation is beneficial to the Singapore economy, even as they acknowledge (77%) that their jobs will be highly impacted by new or changing technologies in the next five years.
In preparing for this impeding disruption, Singaporeans are taking initiatives to prepare themselves for the changes that are expected to arise from automation. 78% of all Singaporeans and 81% of those most in risk of job displacement due to automation have taken measures to upgrade their skills or acquire new ones to prepare for these changes.
While these are encouraging developments, PayPal cautioned that the Singaporean workforce still has a long way to go in preparing for automation and allied changes. “Singaporeans’ financial readiness for technological changes might not be as robust as the programs that have been created for upskilling and getting back to work after displacement. In fact, many Singaporeans have not yet considered the financial implications of changes from automation,” PayPal wrote.
More worryingly, workers in jobs that are at high risk of automation also show more signs of financial distress, with more than half (54%) having paid a bill late and incurred additional fees or interest in the last year, compared to 34% for those in jobs at low risk of automation. The ability of the former group to handle income shocks is also lower, with one-third of them (34%) saying they would be unable to cover three months of expenses with their savings if they lost their main source of income. This figure drops to 23% for those in jobs at low risk of automation.
