Written Answer · 2026-08-04 · Parliament 15
Enhancing Retrenchment Statistics to Capture AI or Automation as Contributing Factors
Nominated MP Sanjeev Kumar Tiwari asked the Acting Minister for Manpower in a written question whether the Ministry plans to enhance its retrenchment statistics to better capture contributing factors such as artificial intelligence (AI) or automation, rather than recording them under the broad category of business restructuring, and if so whether a detailed breakdown by occupational group could be provided, particularly for Professionals, Managers and Executives (PMEs). Acting Minister for Manpower Jasmin Lau replied that it is currently difficult to isolate the impact of AI or automation as a primary driver of retrenchments, because automation is typically implemented as part of broader business transformation or restructuring exercises. The Ministry will continue to study how it can better capture the impact of AI and automation in its retrenchment statistics. The answer gave no timeline for any change and made no commitment to an occupational breakdown.
Why it matters
The Ministry of Manpower admits its retrenchment statistics cannot isolate AI as a cause, so Singapore still has no official data on how much AI is actually displacing PME jobs.
Key Points
- • Tiwari asked for retrenchment statistics to break out AI or automation from the broad "business restructuring" category, with a breakdown by occupational group, especially PMEs
- • MOM said automation is typically embedded in broader business transformation or restructuring exercises, making it difficult at present to isolate AI or automation as a primary driver of retrenchments
- • MOM committed to continue studying how to better capture the impact of AI and automation in its retrenchment statistics, but gave no timeline or commitment to a breakdown
MOM acknowledges a blind spot in its retrenchment statistics but keeps the current classification, arguing that automation is usually embedded in wider business transformation or restructuring and cannot easily be isolated; it commits only to keep studying better ways to capture the effect, with no promise to change categories or provide an occupational breakdown.
Nominated MP Sanjeev Kumar Tiwari's concern is that the broad "business restructuring" category masks the real impact of AI and automation on jobs, especially for PMEs; he wants finer-grained official data so that the effect of AI on white-collar roles can be assessed and debated.
Singapore's official employment statistics do not yet treat AI as a standalone cause of retrenchment. Even as the debate over an "AI transition with no jobless growth" intensifies, MOM remains cautious about quantifying AI's impact on jobs, and any improvement in data granularity is still at the "continue to study" stage — meaning policy debate will lack an official baseline on AI-driven retrenchments for the near term.
"It is currently difficult to isolate the impact of artificial intelligence (AI) or automation as a primary driver of retrenchments as automation is typically implemented as part of broader business transformation or restructuring exercises."
Participants (2)
- Mr Sanjeev Kumar Tiwari
- Jasmin Lau
Original Text (English)
SPRS Hansard · Fetched: 2026-09-04
134 Mr Sanjeev Kumar Tiwari asked the Acting Minister for Manpower (a) whether the Ministry plans to enhance retrenchment statistics to better capture contributing factors, such as artificial intelligence or automation, instead of under the broad category of business restructuring; and (b) if so, whether a detailed breakdown of such cases by occupational group, particularly among Professionals, Managers and Executives, can be provided.
Ms Jasmin Lau : It is currently difficult to isolate the impact of artificial intelligence (AI) or automation as a primary driver of retrenchments as automation is typically implemented as part of broader business transformation or restructuring exercises. The Ministry will continue to study how we can better capture the impact of AI and automation in its retrenchment statistics.