Alfred Olivares
Managing Partner, Healthcare and Life Sciences, HTEC
Artificial intelligence (AI) in healthcare is no longer a futuristic concept; it is an active force reshaping patient care through its integration with medical devices.
From diagnostics to monitoring and treatment support, AI is enhancing how care is delivered and how patients experience it.
The AI-driven medical device boom
The role of AI in medical devices has grown dramatically. A recent BCG report noted that FDA authorisations for AI and machine learning-enabled medical devices have increased more than 35-fold since 2015. By the end of 2023, over 1,000 such devices had been approved. Signalling a clear shift toward more intelligent, data-driven care solutions.
Robotic surgery, for example, is an area seeing rapid development. AI-enhanced tools offer real-time navigation, precision and personalised planning. Transforming orthopaedics and neurosurgery, these AI-integrated systems are increasingly paired with augmented reality overlays and predictive models. As capabilities grow, they promise safer, faster procedures tailored to each patient’s anatomy and clinical context.
Smart support for ageing populations
One of AI’s most profound contributions is empowering seniors to live independently. We partnered with a robotics innovator to develop the next generation of household robotic assistants that combine physical support with AI-driven health insights.
These assistive devices handle daily tasks and medication reminders while monitoring health signals to flag early warning signs. Designed through behavioural engineering and human-machine interaction workshops, they prioritise intuitive use and real-world benefit over force-fitting technology into people’s lives. By sharing relevant data with care teams, these devices reduce hospitalisations and caregiver burden, while preserving patient dignity.
Remote patient monitoring
is another area primed to
benefit from AI.
Transforming patient monitoring and health data integration
Remote patient monitoring is another area primed to benefit from AI. We collaborated with a healthtech provider to integrate machine learning into a mobile health platform, enabling real-time analysis of patient-generated data from wearables, apps and connected devices.
Using predictive models alongside this data to detect anomalies, the platform empowers clinicians to act early and with greater precision. Our team reimagined the interface for both patients and providers, increasing adherence and data accuracy. It reflected what we see as a broader industry trend: transitioning from episodic care to continuous, insights-driven support.
Smarter quality management for safer medical devices
In patient care, compliance complexity grows exponentially as innovation accelerates. Understanding this, we supported a medical device quality management platform in modernising its infrastructure using modular design and the Strangler architecture pattern. This enabled ongoing updates without disrupting clinical use.
We developed an independent, AI-powered risk management module that automates hazard identification and traceability throughout the product lifecycle. This not only enhances safety and transparency today but keeps an eye on tomorrow, as we’ve seen regulators increasingly focus on lifecycle oversight for AI/ML-enabled devices.
Overcoming challenges in AI-enabled care
Regulatory pressures aren’t the only challenges to consider; concerns about data privacy, cybersecurity, algorithmic bias and transparency must be addressed carefully. At HTEC, we prioritise ethical design principles, build robust security frameworks and align with regulatory standards such as HL7, IHE and FDA guidelines.
Crucially, we believe that AI should augment the clinician’s role, not replace it. Medical devices must support decision-making rather than take it over. The human connection in care remains essential.
Future of seamless, intelligent patient care
The future of AI in patient care will be defined by convergence. Technologies like digital twins will enable real-time simulation of devices and treatment plans. AI-enabled diagnostic platforms will enhance precision medicine. Unified data ecosystems will break silos to create seamless, end-to-end care journeys. Remote monitoring will reduce readmissions and enhance access for underserved communities.
A significant share of successful AI adoption lies in cultural change, clinician training and patient trust. These are areas that require just as much innovation as the algorithms themselves. International collaboration will be key to ensuring equitable innovation and consistent safety standards. We’re already building toward this future. Our focus is on creating AI-powered devices that not only meet today’s clinical needs but also anticipate tomorrow’s possibilities.
