Future of Medicine

In Pakistan’s hospitals, AI’s promise isn’t glamour, it’s saving time, lives and dignity

Step into any hospital, and you'll notice the real problem isn't just the crowds; it's the waiting. There's a mother glued to her seat, hoping for an ultrasound report. A diabetic checks his watch, worried his test results won't come in time. Junior doctors dart from file to file, running out of hours and patience. People love to talk about artificial intelligence (AI) like it's some shiny new toy, but the truth is, its real value in medicine comes down to something much more basic, like getting things done faster and more accurately.

The rest of the world is already betting big on this. One market study puts the global AI healthcare industry at $39.25 billion for 2025, jumping up from $29.01 billion in 2024. That's not just numbers on a chart. It means these tools are leaving labs and showing up where they matter: in hospital wards, ambulances, pharmacies, and even at the billing counter.

Let's look closer. In 2024, Pakistan had 319,572 registered doctors. That's more than last year, sure, but it's still not enough. There are 1,696 hospitals and 5,434 basic health units, but the gap between what people need and what the system can handle keeps growing wider. Public health spending only reached 0.9% of GDP in 2024. Total health spending hit 924.9 billion rupees, up from the year before, but the pressure never lets up. When resources are tight, every wasted hour puts lives on the line.

AI can actually help us if used smartly. Take radiology: algorithms can sort chest X-rays, catch signs of TB, even flag possible strokes so doctors focus on the sickest patients first. In pathology, machines spot cancer cells that tired eyes might miss. 

For primary care, AI helps doctors avoid diagnostic mistakes, guides better treatment, and catches warning signs like high-risk pregnancies or sepsis before things fall apart. Hospital logistics get a boost too: predictive systems help plan for bed shortages, cut down on missed appointments, and make sure medicines stay in stock.

But medicine isn't just numbers. We can't just import AI like it's the latest gadget. Medical data is personal. Algorithms can pick up bias, widen the gap between rich and poor, or end up as tools for surveillance. A bad model can do a lot of harm, fast. That's why strict rules matter more than hype.

Our National AI Policy 2025 is a start, but health needs tougher standards: clinical testing before rollout, independent checks for safety and bias, open reporting on how models work in real hospitals, and clear rules for accountability.

Then comes the messy part: data. Too many hospitals still use paper files or old, incompatible software. Without clean, connected records, AI won't work right or worse, it could put patients in danger. The government needs to set national health data standards, create research datasets that protect privacy and require real consent and medical staff training for making AI safer.

Start small. Measure honestly. Only scale up what actually helps patients. Pilot projects like using AI to screen for TB, flag high-risk pregnancies, or sort patients in the ER can show real results fast. The government should back clinical trials, make sure they work in Urdu and regional languages, and build a secure, national health data exchange focusing on safety, privacy, and whether they actually work, not just on flashy brands.

If we treat AI as a tool for public health, not as a trophy for politicians, it can give precious minutes back to exhausted staff, help doctors make clearer decisions, and restore dignity to patients who, right now, pay for every delay with their health.