How medtech can overcome the top challenges of using AI

Our recent survey—conducted in partnership with Microsoft—reveals the top challenges medtech decision-makers face for turning AI enthusiasm into action.

In a recent survey that we conducted in partnership with Microsoft, 86% of medtech decision-makers in the US said they’re enthusiastic about the prospects of artificial intelligence (AI) for their business. But is that excitement driving action?

While it seems almost everyone can agree AI will play a pivotal role in enabling rapid innovation and improving the safety, effectiveness, accuracy and quality control of medtech products, far fewer companies are ready to deploy this technology at scale today. 

In our research, medtech companies spoke to the top challenges of using AI: complex and evolving regulatory requirements, data privacy and security concerns and a mounting talent shortage. 

While there is no easy fix to these issues, our analysis suggests there are effective ways to mitigate them in the short term while also setting up businesses for longer-term success. 

Resolving challenges of AI in medtech

Here are several outside-the-box strategies to help overcome the three biggest challenges facing medtech companies when it comes to AI: regulation, data and talent.

1.    Use existing regulatory frameworks to build the AI muscle that will enable a swift response to future changes. 

The US medtech industry is grappling with growing—and often conflicting—regulatory pressures. As stringent and inconsistent regulations are rolled out across states, many medtech leaders are uncertain about how AI will integrate into this complex landscape.

But companies that take a “wait and see” approach in the name of regulatory uncertainty will miss out on using this technology for competitive advantage. 

There are three things to keep in mind when it comes to navigating the regulatory landscape: 

1. Existing regulatory frameworks are already in place. Rules from the Food & Drug Administration, as well as global regulatory agencies, provide a reasonable foundation from which companies can begin to test and build with this technology. In areas where US regulations are not yet fully mature, the medical device industry may look to the EU’s AI Act, adopted in June 2023, to understand the path to compliance that likely lies ahead in the US.
   
   
2. The regulatory environment is always evolving. In the US, that evolution starts with the White House’s Blueprint for an AI Bill of Rights, which led to an October 2023 Executive Order on the Safe, Secure and Trustworthy Development and Use of Artificial Intelligence across all US agencies. Critically, the executive order may eventually trigger additional reporting requirements for life sciences companies. For example, medtech developers may have to consider not only the FDA’s guidelines but also those of, say, Homeland Security or the Federal Trade Commission.
   
   
3. Ethical compliance is essential. There’s a broader public interest in AI that companies will have to consider when integrating AI in their products and operations. In addition to governmental standards, there will also be social standards driven by non-public and quasi-public groups. Case in point: the Vatican’s AI Ethics Book, which advocates for integrating ethical standards into technology and businesses from their inception.

Our advice is to leverage the established regulatory frameworks to launch training programs that will help get the organization AI-ready. Ensuring AI literacy across teams—whether in product design, engineering or field support—is a crucial step in addressing both existing and future regulations. 

A good resource is Stanford University’s framework for grading compliance of LLMs against the EU AI Act. Medtech companies could use this framework to identify the rules they’ll need to address when introducing AI into their own products.

Medtech organizations should also identify external experts that can serve as partners to guide compliance efforts and help develop the internal policies needed to ensure strong governance, safety and security.

2.    Develop a talent strategy that focuses on the most important roles to fill.

To use AI technologies to their fullest potential, medtech manufacturers need access to not only top-quality AI talent but also behavioral scientists, researchers and ethicists to navigate societal expectations for AI.

The problem, of course, is that AI talent is in short supply—and that’s not even considering the people with the combination of tech skills, human physiology expertise and product engineering experience to lead development for medtech companies. 

Given the high demand for AI talent across all major sectors, medtech companies should consider grouping their workforce needs into two categories: crucial roles that are core to developing and enhancing the company’s intellectual property, and high-tech roles that can be filled via tech and consulting partnerships. By making this distinction, companies will likely find they need to only recruit actively for a handful of highly specialized roles, as opposed to thousands of digital positions.

At the same time, it’s a buyer’s market when it comes to talent. To that end, it’s important to understand what motivates individual candidates and adapt the recruitment process to match those preferences.

For example, financial incentives are no longer the primary motivating factor for prospective talent, especially younger people. Younger workers are often mission- and value-driven, and they want to work for a company that shares their commitment to issues like sustainability, social justice, fairness and inclusivity. For medtech companies, articulating a clear vision of how the company’s work can have a positive impact on the world can help set the organization apart in a high-demand job market.

3.    Focus on the highest standard when it comes to data security, privacy and interoperability.

Since regulations vary from state to state, data privacy and security requirements are especially complex in the US. Rather than attempting to develop specialized strategies for each state, medtech companies should instead develop policies that adhere to the strictest state regulations, such as those in Massachusetts and California, and use those as the foundation for others.

Thinking of security and privacy policies as a uniting factor can also enable a mindset shift that will help strengthen data interoperability. Enabling different stakeholders to share data between systems, applications and devices is necessary for unlocking the real potential of AI and enabling companies across the value chain to better understand everything from treatment protocols to recovery plans to proper diagnoses. All of these could potentially improve health outcomes and reduce healthcare costs.

Taking the first step toward AI in medtech

Incorporating AI into medtech is not a game of wait-and-see—overcoming these challenges will not get easier over time. Fortunately, there are clear and specific steps businesses can take to effectively address market challenges and turn AI enthusiasm into action.

To learn more about the opportunities and challenges of generative AI for medtech companies, download our full research report, co-published with Microsoft: The Future of Medtech: The Role of AI.