FEBRUARY 28 — We hear it all the time. Artificial intelligence is going to make healthcare faster, smarter and more modern. In Malaysia, this is already happening. AI helps shorten waiting times. It helps doctors to read information, supports telemedicine and making decisions in hospitals. On the surface, this sounds like great news. And in many ways, it is.

But here is the uncomfortable question we need to ask: faster for who?

If AI only makes healthcare faster for people who already have good access, then it is not really fixing the system. It is just making a good system better for some, while others are left even further behind. The real promise of AI in healthcare is not just speed. It is fairness. It is about making sure that where you live, how much you earn, or whether you go to a public or private hospital does not decide how good your care is.

In Malaysia, we already know the reality. Healthcare in big cities is very different from healthcare in rural areas. Private hospitals often look and feel very different from public ones. Many of us have seen this with our own eyes. Some people can get scans, tests, and specialist care very quickly. Others wait for months.

When AI enters this picture, it can either help close this gap, or quietly make it wider. In fact, our national leaders have already highlighted this opportunity. As Prime Minister Datuk Seri Anwar Ibrahim said at the World Economic Forum 2025, “Through AI, it not only enhances efficiency and (leverages) sophisticated technology, but it also helps reduce cost wastage... it is grossly unjust... to deny the vast majority (of people) (access to) the best health facilities.” This vision is powerful. But it will only become real if fairness is treated as a priority, not an afterthought.

Right now, new technology almost always goes to big, well-funded hospitals first. This is normal, but it is also a problem. Hospitals in developed cities are more likely to use AI tools for imaging and diagnosis. For example, Johor Bahru's Johor Specialist Hospital expanded AI-driven tech across KPJ's network with its first Da Vinci Xi robotic-assisted gynaecological procedure (“Patient Centricity Elevated with the Introduction of Robotic Assisted Surgery in Johor Specialist Hospital”) and Klang Valley with Qualitas clinics and National Cancer Institute that uses AI. These systems can help doctors spot problems faster and move urgent cases to the front of the line. For patients in these hospitals, this can feel like the future has arrived.

But what about patients in small district clinics in inland areas? Many of these places, like Sarawak, still struggle with basic internet access, old systems, and staff shortages. For them, AI is not “the future.” It is something they hear about, but rarely see. So while some patients get faster, AI-supported care, others are still stuck waiting, sometimes just to get basic tests done.

Cost makes this even more complicated. Advanced AI tools are expensive. Private hospitals can often afford them. Public hospitals, which care for most Malaysians, are under constant pressure. They handle huge patient numbers with limited budgets. If AI becomes something mainly used in private hospitals, then the message becomes clear, even if no one says it out loud: better technology is for those who can pay.

Think about what this means in real life. A patient who can afford private care might get a scan read faster by AI. They might get a cancer diagnosis earlier. They might start treatment sooner. Another patient, relying on a public hospital, might wait much longer for the same test. Over time, this changes more than just waiting times. It changes outcomes. It changes survival. It changes how fair the system feels.

There is also a quieter problem that many people do not talk about enough, which is data bias. AI learns from past data. If most of that data comes from urban hospitals and certain groups, then the AI will naturally work better for those people. It may work less well for rural patients, lower-income groups, or communities that are not well represented in the data. This kind of bias is invisible. Patients do not see it on a screen. But they may feel it in slower diagnoses, missed signs, or less accurate predictions. Over time, this can quietly make health gaps worse, even though the technology is supposed to make things better.

All of this does not mean AI is a bad thing. AI has huge potential. But we need to be honest about one thing: if we only chase speed and shiny technology, we may forget about the people who need help the most. The real success of AI in Malaysian healthcare should not be measured only by how advanced our top hospitals look. It should be measured by whether a patient in a rural clinic gets better care. It should be measured by whether public hospitals are supported, not left behind. It should be measured by whether lower-income families feel that the system is working for them too.

AI should not just make healthcare faster. It should help build a healthcare system that feels fair, caring, and inclusive. One where people believe that no matter who they are or where they live, they matter just as much. That is the kind of future worth building.

* Lim Xin Bei is a final year student at the Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, enrolled in an elective course entitled “Healthcare Technology and Clinical Management”, and may be reached at nahrizuladib@um.edu.my 

* This is the personal opinion of the writer or publication and does not necessarily represent the views of Malay Mail.