AI in drug discovery: will the technology justify Big Pharma's investment?

Pharmaceutical companies are investing record sums in AI-assisted drug development. But one question remains pressing: can the technology live up to investors' hopes and actually speed up the creation of effective drugs?

Big money on AI

Companies such as Pfizer, Merck and GSK are actively funding startups that use AI for drug discovery. Annual investment in this segment has exceeded several billion dollars. Pharma sees AI as a way to speed up the discovery of new molecules, cut the cost of developing a drug and shorten time to market.

The technology promises a real revolution: instead of the traditional 10-15 years to develop a single drug, just 3-5 years. Instead of the standard $2-3 billion in costs, $500 million. For pharmaceutical companies this sounds like a genuine salvation, one that could turn the whole industry upside down.

Where is the real evidence?

But serious analysts and investors are asking an uncomfortable question: where are the actual successes? How many AI-developed drugs have actually passed all phases of clinical trials and won regulatory approval? The answer is sobering: almost none so far.

Most AI projects are still at the very earliest stage: discovering candidate molecules. Getting from an idea to a real drug on a pharmacy shelf is a completely different challenge, one where AI can help very little.

• Most AI projects are at the molecule-discovery stage, long before clinical trials
• There is almost no clinical evidence of effectiveness yet
• Investors are waiting for concrete commercial results, not polished presentations
• In 2024-2025, only a few drugs reached late-stage (II-III) trials

The specific examples are unimpressive

Let's look at specific cases. Exscientia, one of the best-funded AI startups in pharma, has received more than $500 million in investment. But the first drug developed with its AI is still in early clinical trials. No approvals, no wins.

BenevolentAI, another heavyweight in this space, has spent hundreds of millions but has likewise shown no concrete commercial success on the market. These are not small companies but global leaders in AI pharma. Even they are struggling to move from promises to results.

Skepticism is growing in the industry

More and more experienced analysts believe Big Pharma has overestimated AI's potential over the next 5-10 years. The technology is good at finding molecules, of course; that is what AI is genuinely suited for. But after that the real difficulties begin: clinical trials, regulatory approval, proving safety in humans. Each of these stages takes many years and huge sums of money.

AI can help here with data processing, but it cannot answer the central question: does the drug work in people? That requires careful work by doctors, researchers and patients.

"The hype is a few years ahead of reality," investors say, pointing to

the complete absence of commercial successes and actual approved drugs.

Money does not guarantee results

Here is an interesting paradox: even huge investments do not guarantee success. The first AI startups in pharma received hundreds of millions of dollars, yet to this day have not brought a single drug to market. Time passes, cash reserves run low, and there are no concrete results. For investors this becomes a painful issue and a test of confidence. For the companies, it is a real and growing risk of losing face and wasting enormous sums.

What this means

AI in pharma is a useful tool, but not a panacea and not the savior of the industry. Companies need concrete results, not marketing and promises. The next 3-5 years will show whether Big Pharma bought into a real technology or simply invested in an attractive story riding the AI fever.