The Top-Down Strategy Helping Medical Technology Companies Succeed With Gen AI

More than a year into the generative artificial intelligence (gen AI) revolution, we are still seeing huge variability in what adoption actually looks like. Some industries have forged ahead, creating AI-powered solutions to solve real-world business problems; others have been slower to adapt to the sea change. Among the latter group is the medical technology (MedTech) space.

In a sector that produces life-saving clinical software and medical devices, this caution is not without good reason. The industry is both heavily regulated and inherently risk averse, and the stakes are too high for haphazard experimentation. On the other hand, this strict standard of care should simultaneously compel companies to explore emerging gen AI technology that could improve quality of life, detect health problems earlier, and ultimately save lives. 

But unlocking the full potential of gen AI in MedTech isn’t as simple as creating a line item in a budget. “You need to do all the right things to also unlock this value, and not just invest money,” explains Dr. Gunnar Trommer, partner and managing director for BCG X. “Money alone doesn’t lead to ROI.”

In other words, if the burgeoning technology of gen AI is treacherous terrain, MedTech companies need a reliable map. And that’s exactly why Boston Consulting Group (BCG) has developed a new way of thinking that can help lead businesses safely to their destination: measurable business value through AI-powered products and experiences.

As Trommer emphasized, there is the real potential for payoff. “If you invest heavily in gen AI, and do so intelligently, you can shave up to 10 percent off your cost base,” he says. “That’s huge.” 

What Most Companies Get Wrong About Gen AI

According to BCG, most companies assume that gen AI efforts are focused on the technology and tools. Not so. In fact, the vast majority of value lies elsewhere. Trommer, along with Vikram Aggarwal, BCG’s global sector leader for MedTech, calls this the 10/20/70 principle.

“The value doesn’t come from the tools and the technologies alone,” says Aggarwal. “Ten percent comes from the algorithms that support the various use cases, and 20 percent from the tech.” This involves developing and customizing gen AI models to meet specific needs, such as marketing, customer service, and product development.

“What ultimately drives the large part of value is that 70 percent, which comes from people through change management and process overhauls.” This includes training individuals, integrating gen AI into workflows, changing business processes to fully leverage the technology, upskilling employees to use AI tools effectively, and embedding gen AI deeply into the organization.

To realize that value, BCG has developed a three-part approach that drives value for organizations integrating AI and gen AI into their organizations in a range of ways. Here’s a closer look at each segment—and the real-world outcomes that have been powered by each.

Deploy: Implementing Off-the-Shelf Gen AI Tools to Enhance Operations

The first value play of BCG’s approach keeps things simple: Leverage configurable, off-the-shelf tools to enhance everyday tasks. Here, the learning curve is forgiving—and by focusing on operations, you can insulate your company from thorny ethical concerns around the core of your business. Specifically, the focus here is on increased individual productivity.

“When we talk about deployment, we’re talking about à la carte gen AI—tools that readily exist and are configurable to the needs of different MedTech businesses,” explains Aggarwal. Boosting your daily operations with existing tools is the quickest way for a MedTech company to engage with gen AI and see bottom-line results.

For example, BCG has helped MedTech clients harness existing gen AI technology to search and synthesize information from multiple unstructured data sources, including product specifications, customer contracts, and employee benefits manuals. These tools synthesize that complex data in a fraction of the time a human being could, thereby increasing productivity and passing on cost savings to the employer.