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Across Malaysia, organisations now use AI-powered tools to draft emails, analyse data, and automate routine tasks. Many hope AI will improve productivity, support better work-life balance, and help teams keep pace with change.
But as AI use grows, a practical question is emerging in Malaysian workplaces: does AI truly save time, or does it create more rework?
The results suggest that while AI is delivering value for most professionals, the experience is far from uniform.
Many professionals use generative AI to speed up drafting, summarise information, and organise ideas. These tools can support content creation and early-stage thinking, especially when deadlines are tight.
This aligns with the poll findings, where more than two-thirds of respondents report clear productivity gains from using AI at work.
However, the data also reflects a more nuanced reality. Nearly one in five professionals say AI is helpful but creates additional rework, and this is where frustration often emerges. AI output does not always meet business or client expectations, which means employees still spend time reviewing, correcting, or rewriting content to ensure high-quality results. In some cases, this takes as long as doing the task manually.
This “rework effect” shows a clear limit. AI models can support preparation and efficiency, but people still provide judgment, context, and accountability.
In areas such as customer service, customer support, sales, and management roles, human oversight remains essential.
For employers, the poll results reinforce why AI continues to gain traction. With 68% of professionals reporting productivity gains, AI integration clearly has the potential to deliver meaningful value when applied well.
In Malaysia, where teams often operate with limited headcount, these gains matter.
At the same time, the 18% reporting additional rework highlights a leadership challenge. Many organisations introduce AI tools faster than they train employees to use them effectively. Without clear guidance, AI adoption varies widely across teams.
Instead of improving productivity, AI can slow teams down if leaders do not set clear expectations.
While a smaller proportion, the 9% of respondents who do not use AI at work point to an important gap. When AI adoption is uneven, skill gaps grow between team members who use digital tools confidently and those who do not.
In a labour market facing skills shortages, this creates a long-term risk to employability and workforce readiness.
In many cases, non-use reflects uncertainty rather than resistance. Employees may be unclear about what tools are approved, how to use them, or how AI fits into their role.
For employers, this is not just a technology issue. It is a capability and management challenge.
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