AI in MedTech: Why Data Platforms Matter More Than Algorithms. IoMT (Internet of Medical Things)

According to McKinsey’s 2025 State of AI, 23% of enterprises are scaling AI systems and 39% are experimenting with them — yet fewer than 10% have achieved enterprise-wide deployment. In most cases, the challenge is not the model itself but the data infrastructure required to operationalize AI at scale. 

In MedTech, this challenge is even more pronounced. 

The Internet of Medical Things (IoMT) market surpassed $70B in 2025, with connected imaging systems, wearables, monitoring devices, and surgical platforms generating continuous streams of data. At the same time, the FDA has already authorized more than 700 AI-enabled medical devices, reflecting the rapid growth of intelligent diagnostics and AI-assisted clinical technologies. 

This creates three major data challenges for MedTech organizations: 

Volume – IoMT devices generate continuous streams of telemetry and diagnostic data that must be processed in near real time. 

Variety – Data originates from multiple sources including device telemetry, EHR systems, clinical platforms, manufacturing systems, and regulatory documentation. 

Velocity – Data must be analyzed quickly to support clinical decision-making, predictive maintenance of devices, and operational optimization across healthcare systems. 

AI models depend heavily on this data. Without scalable data infrastructure, even the most advanced algorithms struggle to deliver meaningful clinical or operational impact. 

This is why many MedTech companies are rethinking their data architectures. Legacy systems built around fragmented warehouses and siloed pipelines cannot support modern AI workloads, streaming device data, or regulatory-grade governance. 

The shift we’re increasingly seeing is toward modern lakehouse data platforms that unify structured and unstructured healthcare data, enable large-scale analytics, and support the full AI lifecycle — from ingestion and engineering to model deployment and monitoring. 

In the next phase of MedTech innovation, data infrastructure maturity will become a key competitive differentiator. 

The organizations that can unify device, clinical, and operational data into scalable platforms will be the ones that successfully operationalize AI across their products and healthcare ecosystems. 

Because in the era of intelligent medical devices, success won’t be defined by algorithms alone — it will be defined by the strength of the data platforms behind them.