84% of Malaysian knowledge workers said they used AI at work in 2024

Artificial intelligence was already part of everyday work for many Malaysian knowledge workers by mid-2024, according to the Malaysian findings of Microsoft and LinkedIn's Work Trend Index. The companies reported that 84% of the surveyed group used AI at work—nine percentage points above the 75% global result.[1]

The number was not a national census. The broader research covered 31,000 people in 31 countries and combined survey responses with LinkedIn, Microsoft 365 and customer research signals. Microsoft Malaysia did not state its local sample size, so 84% should be read as a finding about surveyed knowledge workers rather than all employees.[1]

Even with that limitation, the results exposed a useful tension. Staff adoption was high, yet employers were still working out policy, training and business value. Leaders saw AI as necessary for competitiveness but lacked a clear route from individual experiments to managed use at scale.[1]

Microsoft and LinkedIn said 88% of Malaysian leaders believed their company needed to adopt AI to remain competitive. At the same time, 66% worried that organisational leadership lacked a plan and vision for implementation. That combination matters: executive agreement about the direction of travel does not automatically produce approved tools, safe data practices, redesigned workflows or a way to measure whether the technology improves an outcome.[1]

K Raman, then managing director of Microsoft Malaysia, said workers were using AI without waiting for a coherent organisational roadmap. Employers still need to distinguish casual use from repeatable business transformation. A useful deployment has an owner, a defined task, data boundaries, human review and an outcome baseline.[1]

Among Malaysian AI users surveyed, 83% said they brought their own AI tools into work. This behaviour, described in the report as BYOAI, can arise when employees find a useful tool before their employer has selected an approved alternative. It can accelerate learning, but it also means customer data, internal documents or confidential business details may move through services that the organisation has not assessed or configured.[1]

A blanket ban does not explain which tasks are safe or provide a better workflow. A practical SME response is to map tools already in use, identify the information staff enter, approve a small set of services and define where a human must check the output. This turns scattered experiments into a more reliable operating practice.[1]

The Malaysian leadership responses suggested a substantial change in how candidates could be assessed. Microsoft and LinkedIn reported that 62% of Malaysian leaders would not hire someone without AI skills. Another 65% said they would rather hire a less experienced candidate who had AI skills than a more experienced candidate who did not. These are stated hiring preferences from the survey, not proof that the same percentages of actual hiring decisions followed that rule.[1]

Rohit Kalsy, LinkedIn's Southeast Asia emerging-markets sales head at the time, framed AI competency as a workplace necessity. But a CV line naming ChatGPT or Copilot is weak evidence. A better assessment asks how a candidate chose a tool, protected information, checked the result and improved a real task.[1]

The report defined an AI power user as someone who used the technology several times a week and saved more than 30 minutes a day. In Malaysia, 85% of these users said they frequently began the day with AI, while 82% used it to plan the next working day. The release also said Malaysian power users were more likely to hear from their chief executive about generative AI, but the uplift in receiving training tailored to their role was much smaller.[1]

General prompting classes may help people start, but finance, sales, operations and human resources face different data and accountability requirements. Training should attach to an approved workflow and measurable standard. The release cited PNB and Johor Corporation as adopters whose executives described AI as part of broader skills, culture and operating change.[1]