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Across Singapore, artificial intelligence is becoming part of everyday work. Many organisations now rely on AI-powered tools to draft emails, analyse data, and automate routine tasks. The goal is clear: improve workplace productivity and help teams work faster.
But as AI at work becomes more common, many employers and employees are asking a simple question. Does AI save time, or does it create more rework?
A recent LinkedIn poll by Hays among professionals in Singapore highlights a more divided experience. Of the 62 respondents, 55% say AI saves them time and boosts productivity, while a notable 31% say it is helpful but adds extra rework. A smaller group — 5% — feel AI creates more hassle than value, and 10% do not use AI at work at all.
The results suggest that while AI is delivering benefits for many, a significant portion of professionals are still experiencing friction.
Many professionals use generative AI to support content creation, early drafts, and basic analysis. These tools help people start tasks faster, especially in fast-moving environments.
This aligns with the poll results, where more than half of respondents report productivity gains from AI.
However, the higher 31% who say AI adds rework reveals an important tension. Employees often find that AI-generated output still needs refining to meet business standards, client expectations, or regulatory requirements. Reviewing and correcting AI output can reduce — or even cancel out — the time saved upfront.
This “rework effect” shows a clear limit. AI models can support speed and efficiency, but people still bring judgment and accountability.
In areas such as customer service, customer support, and leadership roles, human oversight remains essential.
From an employer’s point of view, the poll results explain why AI adoption continues to accelerate. With 55% of professionals reporting productivity benefits, AI clearly has a role to play in improving efficiency.
In Singapore, where efficiency matters, these gains are attractive.
However, the 31% reporting additional rework signals a leadership challenge. Many organisations introduce AI tools faster than they equip employees with clear guidance on how to use them well. As a result, AI adoption and output quality can vary widely across teams.
Lack of standards affects trust
Without structure, AI risks becoming another source of inefficiency rather than a productivity enabler.
While a smaller group, the 10% of respondents who do not use AI at work point to an important issue. Not everyone uses AI at work. When this gap grows, some employees move ahead faster than others.
Over time, this can affect employability and workforce readiness in Singapore.
In many cases, non-use reflects uncertainty. Employees may be unclear about approved tools, expectations, or how AI fits into daily work. This makes AI a people and management issue, not just a technology one.
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