For much of her early career, Shobie Ramakrishnan called Silicon Valley home. GSK’s chief digital and technology officer (CDTO) worked for years at tech giants like Apple and Salesforce before making the switch to the increasingly tech-savvy pharmaceutical sector.

However, while her experience was invaluable in taking on the role of GSK digital chief, Ramakrishnan was aware of its potential pitfalls.

“We don’t do tech for tech’s sake. I’m not trying to turn GSK into Google. We are really keen to produce exceptional medicines and vaccines,” Ramakrishnan told Fortune.

The pharmaceutical sector has undergone a miraculous shift in the past decade, with multibillion-dollar companies leveraging AI for drug discovery and optimization of supply chains. The sector has been able to utilize data that was long left untouched owing to poor technology systems.

The early results have included faster drug discovery, highly optimized supply chains, and greater awareness of consumer demand.

For GSK’s Ramakrishnan, who has served as CDTO since 2021, the biggest challenge was helping her company get a head start in this revolution. Ramakrishnan has been named to the 2024 list of Fortune Tech Leaders: Europe’s Most Influential Women.

GSK’s game-changing opportunity

“There was a recognition in our industry that data was a game-changing opportunity,” said Ramakrishnan.

“It’s always been about data, but [there was] the recognition that data is the golden thread that could help us drive the digital transformation of our business. We had to rewire the organization, set it up for success, build our capabilities, and build our platforms.”

That involved working with GSK’s R&D, supply-chain, and commercial units, to use data in a way that made sense for the company.

Ramakrishnan says the company was an “early thinker” in ensuring data science, data engineering, and AI systems were built in-house.

She said: “We felt like we built it ahead of when it was needed, and therefore when the opportunities came, we were able to deploy it at scale quite effectively, and we’re seeing results from it already.”

Those results have been realized across R&D, supply chains, and commercial areas, Ramakrishnan says.

Improved tech capabilities are expected to help reduce the $2.3 billion average cost of bringing a drug to market, in addition to improving the typical 90% failure rates of trial medicines.

Ramakrishnan used the example of GSK’s work against chronic hepatitis B, with new data capabilities helping the group understand how different patients will react to medication, improving the predictability of clinical trials.

Using 60 digital twins across the company, GSK is also able to map out production needs at its site, simulate different production scenarios, and highlight inefficiencies in the manufacturing and shipping process. With GSK shipping 500 million vaccine doses and up to 1.8 billion packs of medicine last year, the scalability benefits are clear.

Getting employee buy-in

A challenge not isolated to the pharmaceutical sector is getting employees less acquainted with AI enthusiastic about utilizing the tech in their day-to-day.

GSK runs annual conferences focused on upskilling employees’ data capabilities. Initially intended as small events, dubbed “data cons,” for between 400 and 500 workers, such trainings today engage 10% of GSK’s approximately 70,000 employees, Ramakrishnan notes.

“We have continuously made our data con and our digital fluency programs quite robust, and it’s the interest from the teams that … tell us that people really care,” says Ramakrishnan.

“It’s true for everyone, but I think the competitive advantage comes from how you do it, whether you’re able to do it at scale, and whether you’re building talent and capabilities.

“This means that we can truly reimagine what’s possible for patients and society in profound new ways.”