The Dire Need for AI Knowledge: Why Understanding AI Matters More Than Ever

In the same way – electricity once revolutionized industries and homes, Artificial Intelligence (AI) is now becoming the invisible current powering our daily lives. From navigating traffic using Waze to personalized recommendations on Netflix or Shopee, we are surrounded by AI often without even realizing it.

But here is the twist: while many enjoy the convenience AI offers, only a small percentage truly understand how it works or the opportunities it creates. As Malaysia continues to push forward its digital economy agenda, the need for AI knowledge is no longer reserved for tech professionals, it is becoming a societal necessity.

The AI Wave Is Already Here

According to Malaysia Digital Economy Corporation (MDEC), AI is expected to contribute up to RM57 billion to Malaysia’s GDP by 2030 through productivity improvements and innovation. Meanwhile, the Ministry of Science, Technology and Innovation (MOSTI) through its National AI Roadmap 2021- 2025 emphasizes that foundational AI skills must be widespread to ensure Malaysians are not left behind in the digital era.

Yet, many workers particularly in non-tech sectors still view AI as “too complicated” or “not relevant” to their roles. This is where the gap lies: while AI is making decisions behind the scenes in banking, healthcare, logistics, and even agriculture, the people affected by these decisions are often not equipped to understand or challenge them.

From Buzzword to Basic Skill

The idea that AI knowledge is only for engineers is outdated. In fact, understanding AI is fast becoming a basic literacy skill just like learning to use Microsoft Office in the early 2000s.

A basic AI course breaks down these concepts for everyday learners. It gives insight into how AI works, its real-world applications, and the ethical challenges it presents, from algorithmic bias to job displacement.

Moreover, such course also teaches practical tools like Python, TensorFlow, and scikit-learn, skills that are no longer just “nice to have” but are now critical for data-driven roles across industries.