Session 3: How Healthcare CEOs Are Embracing AI

We brought together CEOs from across the healthcare industry, hailing from biopharma, pharma sciences, medical devices, and diagnostics, to hear how they were actively piloting, adopting, and implementing AI technology. Here is what we learned.

Three key takeaways from our conversation with healthcare CEOs who are actively piloting, adopting, and implementing AI technology:

How healthcare CEOs are adopting AI

AI has the ability to narrow healthcare’s historical 20-year lag between innovation and the standard of patient care, including through the use of hyper-personalization and leveraging greater productivity across the ecosystem, from R&D, to manufacturing and supply chain, to marketing. One CEO highlighted: “A key area of interest will be observing the integration of AI with the humanization of healthcare.”

CEOs also shared how AI is allowing the company to scale product development, and helping the company to achieve high levels of productivity and cost points. Another shared how Gen-AI helps drive marketing productivity, allowing their company to advertise at 1/1000th of the historical cost.

Key lessons from healthcare CEOs actively adopting AI

Lesson 1: The greatest risk of AI is inaction

The change that AI will bring to healthcare organizations is vast, and entire business models will need to be reimagined. CEOs discussed that adoption of AI in healthcare is challenging, with risks around disintermediation, cybersecurity, the regulatory environment, the acquisition and retention of technology talent, lack of digital maturity, and culture change and resistance. One CEO also referenced the challenges of keeping the value in their company, rather than letting it leak to technologically savvy customers.

The main risk flagged was the pace required to keep up with the AI disruption. As one CEO shared: “This wave is moving very, very fast—faster than the mobile wave and faster than the Internet wave.” Attendees spoke about the threats of being radically disrupted, outperformed, or falling behind the competition, noting that the AI opportunity available to them was also available to their competitors. One CEO stated: “The risk is not leaping on the opportunity of AI quickly enough.”

Lesson 2: Traditional data stacks will need to evolve to harness AI's potential 

CEOs highlighted how successful adoption of AI requires simultaneous changes in technology architecture and innovation processes. AI provides the opportunity to process incredible amounts of data and couple proprietary data with externally available sources (data twinning) e.g. scientific and clinical data, or multiple sets of patient records, which previously would have been analyzed in isolation. It was accepted that traditional siloed data stacks must evolve into more integrated and agile frameworks to fully harness AI's potential—although this is only part of the equation.

One CEO shared: “We have gotten over the challenge of ensuring our data is organized in the right way, but having people that understand core business processes and what we're trying to accomplish with AI is a challenge. It's gotten so siloed for so long that we don’t have people with the broad perspective that’s needed to manage across historical silos.”

Two CEOs spoke of their radical tactic of building a new tech stack from scratch adjacent to the organization and integrating it, rather than opting for a protracted systems update and multi-year transformation. Building a brand-new team allowed both organizations to set up a whole new platform in record time.

One shared: “We started our AI journey about seven months ago. Bringing people along was very slow and resistance was high. Instead of trying to lean our processes, change our people, and build the tech stack in parallel, we hired one hundred new people. We now have the AI tech stack and the processes all in one place and we get to see how the future works. We’ve built this for three functions. If the model works, we’ll run it through a dozen other functions.”

Lesson 3: The learning capacity of senior leaders is key to AI success

AI is firmly seen as a CEO mandate, with RRA’s AI Practice lead Fawad Bajwa explaining, “Unlike the role of digital transformation, where you may have had someone you delegated this to, AI tech transformation at the level we're talking about lands squarely on the CEO's lap.”

CEOs are in the process of not only personally upskilling around AI, but also ensuring their senior leadership team understands its potential for business applications. Getting senior leaders more fluent in AI would allow them to think outside the box about how AI could be applied.

One CEO shared: “AI has to be a top-down mandate [from the CEO], driven by the functional leaders so that it flows through every part of the organization. The real question is how to get all the leaders in the organization to think about how AI can fundamentally change every part of the business and come up with their own use cases. We can’t be limited by what's out there today because it’s still early days. We need to find ways to get them to want to learn more about AI and to push the envelope.”