If you’re a life science student or professional wondering where the pharmaceutical and healthcare industries are headed, here’s the honest answer, AI is no longer optional. It’s already shaping how drugs are discovered, tested, and brought to patients, and it’s doing so faster than anyone expected.

Let’s talk about what’s actually happening, without hype.

AI is already discovering real medicines

One of the biggest signals that AI has arrived in pharma is Rentosertib, a drug developed by Insilico Medicine. What makes it special is simple but powerful, it is the first drug entirely discovered and designed using artificial intelligence.

This drug targets idiopathic pulmonary fibrosis, a serious lung disease that kills tens of thousands of people every year. In Phase 2 trials, patients showed improved lung function with fewer side effects, and the results were strong enough that the drug is expected to enter Phase 3 trials soon, the final step before regulatory approval.

What usually takes 4 to 5 years just to reach human trials happened here in less than 2 years. Insilico screened only 78 molecules using AI, instead of thousands through traditional trial-and-error methods.

For students, this sends a very clear message, AI is not a future experiment, it’s already producing real medicines.

Why pharma companies are betting big on AI

This shift isn’t happening in isolation. Money, infrastructure, and talent are all moving in the same direction.
Here’s what the industry looks like right now:

• Venture capital invested $2.7 billion in AI-driven drug discovery companies in just the first three quarters of 2025

• Global pharma spending on AI is expected to grow from $2.5 billion in 2026 to over $16 billion by 2034

• Major pharma companies are building dedicated AI infrastructure, not small pilot projects

For example, Eli Lilly partnered with Nvidia to build a massive in-house supercomputer with over 1,000 GPUs. This “AI factory” will simulate and test millions of drug candidates digitally before they ever reach a lab bench.
This means pharma companies are no longer asking if AI works. They’re asking how fast can we scale it.

New job roles are emerging in pharmaceutical healthcare

As AI becomes central to pharma R&D, the kinds of roles companies hire for are changing.
Some examples of AI-influenced job roles include:

• AI-enabled drug discovery scientist

• Bioinformatics and computational biology specialist

• Clinical data scientist

• Gen-AI application engineer for healthcare

• Translational research analyst using machine learning

These roles sit between biology, data, and computation. Traditional wet lab skills alone are not enough anymore. At the same time, pure AI engineers without biological understanding also struggle.
The sweet spot is life science professionals who understand AI.

Why life science students should start learning AI now

If you are studying biotechnology, pharmacy, bioinformatics, or related fields, here’s the reality:

• AI is already reducing discovery timelines

• AI is changing how clinical trials are designed

• AI is influencing regulatory submissions and safety analysis

• AI is becoming part of everyday pharma workflows

Waiting until “later” to learn AI puts you at a disadvantage. Companies are hiring people who can work with AI systems today, not those planning to learn it someday.
Learning AI doesn’t mean becoming a software engineer. It means knowing how to apply AI to biological and healthcare problems.

How to realistically build AI skills for pharma and healthcare

The most effective way to learn AI for pharmaceutical healthcare is through programs that are built specifically for life science learners, not generic tech courses.

This is where Bversity’s PG Programme for Gen-AI in Life Science & Healthcare fits in naturally. The program is designed to help learners:

• Understand how AI is used across drug discovery, genomics, and healthcare data

• Work on real-world healthcare and life science use cases

• Build skills aligned with actual pharma and healthcare job roles

• Bridge the gap between biology and modern AI tools

For students aiming to enter AI-driven pharmaceutical roles, structured learning like this can significantly shorten the path from classroom to industry.

The bigger picture for your career

AI is not replacing life science professionals. It is changing what it means to be one.
The professionals who will thrive are those who can:

• Understand biology deeply

• Use AI tools confidently

• Think in terms of systems, data, and outcomes

Pharmaceutical healthcare industries are moving fast, and they need people who can move with them.
Learning AI today is not about chasing trends. It’s about staying relevant in an industry that is already transforming.