Generative AI in Healthcare: Transformative Technology or Productivity Play?

We've all heard the bold predictions on generative AI's (GenAI) potential to advance healthcare on a global scale. For example, by 2025, more than 30% of new drugs and materials could be discovered using GenAI , and technologies such as conversational AI, smart alerts, and communication auto-drafting have the potential to speed up clinical trial enrollment by 10-20% .

These projections are exhilarating, showing just how far we might go in bringing together technology and science. At the same time, we have to keep in mind that GenAI is at the peak of the hype curve. Remember the metaverse? If expectations for that had played out, we'd all be interacting as avatars today.

The reality is that AI is a much broader capability, so we need to consider the scale of its impact holistically. By bringing traditional AI, machine learning, and GenAI together – along with enablers like data, upskilling efforts, and governance – I believe that we will see the promise of this technology come to life.

I recently attended HLTH Europe , where these topics rightly held center stage. In several conversations, both on- and off-mic, I shared my thoughts around this game-changing technology, the key aspects needed to unlock its potential, and how we’re responsibly implementing it at 强生公司 . Here are my key takeaways.

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Separating the hype from reality

In less than two years, popular GenAI platforms have brought this technology into the mainstream and positioned it as an important option in our toolbox to meaningfully impact the lives of patients globally.

Today, most uses of GenAI in healthcare are geared toward productivity. For example, at J&J, we’re using GenAI (always with a human in the loop) to:

●????? Speed up medical insights by taking in large quantities of scientific research and identifying topics and trends

●????? Help respond to questions from healthcare providers more quickly

●????? Enhance the quality and efficiency of evidence generation to meet specific market requirements, like the Health Technology Assessment process in Europe

Looking forward, we see potential to leverage GenAI in transformational ways by combining its power with our scientific expertise and finding solutions to big questions that can advance our impact on patients.

One of the most exciting opportunities that came up repeatedly during HLTH Europe? Drug discovery.

Even as traditional AI and machine learning have advanced this space, 85% of protein targets are still beyond the reach of current medicines . Just think of how much progress we can make by applying GenAI to help discover, prioritize, and optimize potential drug candidates.

As these use cases move from exploration to outcomes, I think we’ll all be able to confidently say that GenAI is much more than hype. To activate its potential, it’s imperative to remember a critical factor – data.

Data is key to unlocking GenAI’s potential

Having access to trustworthy Findable, Accessible, Interoperable, Reusable (FAIR) data is the foundation of responsible AI in healthcare. The good news is that there is no lack of available healthcare data:

●????? The amount of data generated in healthcare has been increasing at a rate of 47% per year.

●????? The World Economic Forum estimated that the global healthcare sector generated more than 2,300 exabytes of data in 2020. To put that in perspective, that’s about 69 billion 4K movies, or 138 billion video games, or 17 trillion MP3 songs.

So, how can we make sure that data can fuel the use of AI for the good of patients around the world?

I believe that AI in healthcare will be most impactful if we encourage international cooperation in data governance that drives connectivity, interoperability, and greater data quality. That’s why the industry needs to come together to support the creation of trusted health data sharing ecosystems at a national, regional, and global level.

A major leap was the founding of the European Health Data Space (EHDS) . The EHDS will enable the European Union to fully benefit from the potential offered by a safe and secure exchange, use and reuse of health data to benefit patients, researchers, innovators, regulators and policy makers.

Trust will be a fundamental enabler for the success of the EHDS. By working together across stakeholders, we can harmonize and standardize approaches to data that protect privacy while also unleashing innovation to help us answer the big questions, find the needles in haystacks, and turn huge amounts of data into precise insights that help patients, as well as the entirety of our healthcare community.

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Preparing people to bring GenAI to life

With the right models, data, and foundational technologies in place, there’s one more critical factor to consider in a GenAI strategy – people.

Throughout my career, I’ve found that there are typically nine detractors for every one promoter when you’re looking to make a large-scale technology change. So, how we manage this change will play a major role in whether GenAI in healthcare delivers on its promise or fizzles out as just another fad.

To be successful, we need education. We must ensure that people working in our industry understand how to use emerging technologies, whether they’re a healthcare provider, researcher, supply chain engineer, or commercial executive. Through education and awareness, we can give people the knowledge to reimagine the work they do with the help of GenAI.

We also need to consider governance. If we do 1,000 experiments and none of them can scale, we haven’t moved the needle. At Johnson & Johnson, we’ve implemented a robust governance model to ensure we’re testing and learning in a coordinated manner, allowing us to focus on the most promising use cases and avoid chasing the next shiny thing.

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Where do we go from here?

After attending HLTH Europe, I was energized by the diverse perspectives I heard. It will take all of us to bring about the change we want to see with this new technology, and more importantly, to achieve our common goal of improving patients’ outcomes globally.

With the number of smart people in healthcare who are working to harness GenAI in innovative ways, I’m more optimistic than ever that we might just see all the bold predictions turn into reality.