Medtech's digital experience is ready for an upgrade

For years, medtech companies have treated the digital experience around their devices as an afterthought. A layer of software bolted on after the hardware was designed, engineered, and approved. That approach no longer holds up. In the AI era, the way clinicians, patients, and health systems interact with a device is no longer secondary to the device itself. It is the device. The digital experience is becoming an increasingly important part of the product.

To operate successfully going forward, medtech companies need to hold their software experience design to the same standard as the best digital products people use every day; anything less risks disengagement, poor adoption, and, at worst, patient harm.

Why digital experience is now a safety issue, not just a convenience

Clinicians who grew up on intuitive consumer software have little patience for the clunky, counterintuitive interfaces still common in clinical settings. Patients increasingly expect the same seamlessness from their care as they get from everything else in their digital lives. And health systems, under constant pressure to do more with less, depend on tools that reduce friction, rather than add to it.

When digital experience design falls short, the consequences compound quickly. Confusing interfaces contribute to cognitive overload for already-stretched care providers. Poor usability suppresses adoption, meaning even clinically sound technology never delivers its intended value. In the worst cases, poorly designed interfaces can become a factor contributing to medical errors.

Seen this way, good UX isn't a nice-to-have. It's a risk mitigator; not simply because it makes technology easier to use, but because it can help reduce friction and support safer interactions between clinicians and increasingly complex systems. Medtech companies that continue to treat digital experience as a downstream, cosmetic concern are underestimating how directly it affects real-world outcomes.

AI turns devices into data-driven platforms

The industry has talked about value-based care for years, often without a clear mechanism to accelerate it. AI, paired with connected devices, offers an increasingly important approach to accelerate that shift.

When devices are designed with AI and data infrastructure as core components, rather than afterthoughts, they stop being single-purpose tools and start becoming continuous sources of value for everyone touching the care pathway. Properly captured, processed, and analysed, device data can inform clinical decision-making in real time, surface patterns that would otherwise go unnoticed and give health systems a clearer picture of both patient outcomes and operational efficiency.

This requires a mindset shift. Historically, medtech companies have treated the device as the product and the data it generates as a byproduct. That hierarchy needs to change or at least equalise. When data is treated as important as the device itself, it becomes possible to build genuine value-based relationships with providers and payors, not just sell hardware. The device becomes a platform for ongoing value, rather than a static, one-time transaction.

Companies that make this shift will be positioned to compete on outcomes, not just specifications. Companies that don't will find it increasingly difficult to differentiate in a market where "smart" and "connected" are quickly becoming table stakes, rather than selling points.

Balancing innovation with engineering and regulatory reality

None of this happens in a vacuum. As medical devices become more software- and data-driven, manufacturers must navigate regulatory considerations that extend beyond the traditional hardware development process. Becoming digital first doesn't necessarily mean moving fast and breaking things, but it does mean building organisations that can innovate rapidly on the experience layer, while still meeting the rigour that patient safety and regulatory bodies demand.

That's a genuine engineering and organisational challenge. It requires product, design, and engineering teams to work closely with regulatory and quality functions from the earliest stages of development, rather than treating compliance as a final gate to clear before launch. For AI-enabled devices, that lifecycle must also account for issues such as data quality and bias, algorithm transparency, software validation, cybersecurity, and how performance is monitored after deployment.

It also requires medtech companies to build the internal capability to manage software and AI systems that may evolve through controlled updates, retraining, and refinement in a way that traditional hardware development cycles were never designed to accommodate.

The challenge is particularly acute when AI systems must perform reliably across different patient populations and real-world conditions. Data quality, model performance, and potential bias cannot be treated as one-time considerations; they must be addressed throughout development and post-market monitoring.

This is not a trivial undertaking, and companies shouldn't underestimate the time and organisational change it will take to get there. But medtech companies that invest now in building this capability, by treating regulatory and engineering considerations as integrated parts of the design process, rather than separate tracks, will be far better positioned than those that try to retrofit AI and digital experience onto legacy development models later.

Digital first is becoming the baseline, not the differentiator

The direction of travel is clear. Digital-native clinicians and increasingly digital-savvy patients will keep raising their expectations. Health systems will keep looking for partners who can demonstrably improve outcomes and efficiency, not just supply equipment. And AI will continue to make it possible and increasingly expected for devices to deliver value well beyond their original clinical function.

Medtech companies have talked about becoming digital first for years. Companies that treat it as a genuine product principle embedded in how devices are designed, built, and engineered from the outset will earn preference from clinicians, patients, and health systems alike. Those that continue to treat digital experience as secondary to hardware will find that gap increasingly difficult to close.

The moment to address these gaps and redesign for an AI-native era is now. The medtech companies that recognise this – and act on it – will define what the next generation of care delivery looks like.

About the author

Greg Killian is a senior vice president and head of the Life Sciences and Healthcare businesses at EPAM. In this role, his responsibilities include strategy, go-to-market functions, vertical partnerships, and M&A to deliver value to clients, growth, and profitability across the sector. He has over 30 years of experience in Life Sciences and Healthcare technology, bringing deep expertise and proven outcomes in global business, engineering, and leadership. Killian holds a Bachelor of Science in Mechanical Engineering from Villanova University and an MBA from the University of Massachusetts.