Picture this: An MRI machine that adjusts in real-time for personalized scans. A robotic surgery system that adapts, based on patient conditions, during procedures for precision and safety. Patient monitors that collate sensor data with their lifestyle, historical, diagnostic and imaging data to enable AI-driven tailored and precise patient care.
This isn’t science fiction. It’s the emerging reality of modern healthcare system.
From hardware to algorithms
The real differentiator in the new world isn’t in precision hardware anymore. It’s in the algorithms.
We are already seeing this play out in AI-powered diagnostic tools that are detecting cancer earlier, often performing better than human experts. Adaptive insulin pumps now adjust dosing in real time based on individual patient response. Chronic Obstructive Pulmonary Disease (CoPD) is now managed in real time, with data trained to individual patient’s baseline.
This shift is not just reshaping devices, but the definition of care itself. Care no longer needs to be one-size fits all, but can become data-driven, patient-specific and dynamic.
Medical device manufacturers are increasingly recognising software as a critical enabler to delivering intelligent, more responsive care at the point of need. This transition from a purpose-built device to a software-defined platform requires an all-around transformation.
Architectural transformation — from hardware-dependent to software-defined.
Historically, hardware and software were tightly coupled. This led to rigid systems that were costly to update and difficult to scale. To remain agile, competitive, and future proof, companies must now treat devices as modular ecosystems — where software can evolve independently of hardware. Just like smartphones, future medical devices could run apps and receive regular updates to enhance their features, without compromising on the regulatory aspects.
Lifecycle transformation — Reinvent product cycles for the software era
As per McKinsey's analysis, AI is accelerating the development of software-defined hardware through AI-assisted design, software-hardware co-development, hardware optimization, and accelerated testing. This shift is essential as software-first devices require faster, more responsive product cycles that respond to real-world events and continually refine themselves.
Even regulators are adapting. The FDA, MHRA and others are beginning to support clearly defined update pathways, easing the burden of re-approval for safe, incremental changes and patient safety. That said, agility must be balanced with accountability. Companies must invest in systems that track clinical outcomes, monitor algorithm changes, and ensure that every update is safe, validated, tracked and transparent.
Implemented correctly, 'shadow mode' - a parallel environment where new updates or changes can be tested and validated without impacting the actual functionality of the device, can lay the groundwork, making these advanced systems not only smarter with each update, but also safer. The devices can learn from experts and drive continuous improvements across the entire fleet, making device get better everyday.
In the software-defined world, traceability isn’t a compliance requirement — it’s a competitive advantage.
Transform commercial models — Move from devices to outcomes
This device transformation opens up new commercial models: Instead of one-time device sales, companies can now build recurring revenue streams through subscriptions or usage-based pricing. Devices become part of a broader component of the healthcare ecosystem, that can now leverage the component that best addresses what the patient needs.
However, these new commercial models require a different kind of infrastructure. Manufacturers must think like tech companies — equipped beyond traditional sales with module-specific billing systems, device telemetry, customer support, and privacy safeguards.
The Path Forward: Leverage Proven Technical Expertise
To thrive in this new era, MedTech companies must do more than adapt — they must lead with a software-first mindset. This shift goes beyond reimagining a single device. It requires the standardization of engineering across an entire portfolio.
To ease into this transition Wipro’s CloudCareAI enables transformation of your devices into a software-defined platform.
