Software as a Medical Device (SaMD) Market 2025

Software as a Medical Device (SaMD) — From Niche Software to Healthcare’s Digital Backbone

Standalone medical software that performs a medical purpose without being embedded in or controlled by a traditional hardware device is increasingly recognised as Software as a Medical Device (SaMD). As digital health infrastructure matures and regulators articulate clearer paths, SaMD is becoming a core driver of value in healthcare delivery, diagnostics, monitoring and therapy.

This transformation is propelled by three inter-locking forces: artificial intelligence (AI)/machine-learning (ML) innovation, regulatory momentum, and the shift to outcome-based, remote care models.

Why 2025 Is a Tipping Point for SaMD

• According to the U.S. Food & Drug Administration (FDA), AI/ML-enabled medical devices (including SaMD) are at the heart of its “Artificial Intelligence in Software as a Medical Device” initiative, which emphasises lifecycle monitoring, transparency and good machine-learning practices.
• A 2025 review found 1,016 authorizations of AI/ML-enabled medical devices by the FDA as of December 20, 2024 — underscoring how software-based medical devices are rapidly accelerating.
• With nearly 84% of these devices using images as input data, and the majority reviewed under radiology panels, the field continues to expand beyond imaging into monitoring, analytics and real-time decision-support.

These trends show that SaMD is no longer a fringe category — it is central to digital health strategies, and companies must pivot accordingly.

Regulatory Momentum — The Frameworks Aligning for SaMD

Regulation was once a barrier for pure-software medical devices. Today it is a driver:

• The U.S. FDA's approach
  • The FDA clearly defines software that “performs one or more medical purposes without being part of a hardware medical device” as SaMD in its discussion paper.
  • The FDA’s Digital Health Center of Excellence publishes guidance on AI/ML SaMD, including documents such as Good Machine Learning Practice, Predetermined Change Control Plans and Transparency for ML-Enabled Medical Devices.
  • Regulatory datapoint: as of August 2024, ~97% of AI/ML-enabled medical device clearances followed the 510(k) pathway, with only a small minority going through De Novo or PMA.
• Global harmonisation and SaMD
  • The International Medical Device Regulators Forum (IMDRF) provides a global SaMD definition and risk categorisation framework, facilitating converged regulation.
  • The European Union addresses SaMD under Regulation (EU) 2017/745 (MDR) and software-specific provisions; devices that perform diagnostic or therapeutic functions via software qualify.

Why this matters for companies

• Regulatory clarity reduces uncertainty — making SaMD investment less risky.
• Lifecycle regulation (for AI/ML) means that software updates and continuous learning must be controlled, documented and demonstrated — favouring players with mature data, model-governance and quality systems.
• For decision-makers: aligning SaMD strategy now avoids being caught later by new regulatory demands, post-market surveillance or real-world-performance requirements.

AI/ML Innovation — The Technology That Powers SaMD

The role of AI/ML in SaMD

• AI/ML allows SaMD to learn and adapt from data, enabling functions such as image interpretation, risk-prediction, workflow triage and home-monitoring analytics. At the heart of many SaMD innovations is the software’s ability to derive insights from large datasets.
• The taxonomy of 1,016 FDA-authorized devices revealed the predominance of imaging input (84.4%) and a slowdown in growth of purely signal-based devices — suggesting the “low-hanging fruit” of diagnostics is maturing and new frontiers (home-care monitoring, EHR analytics) are emerging.

Use-cases driving uptake

• Radiology AI: Hundreds of cleared devices assist radiologists in flagging findings (e.g., intracranial hemorrhage, pulmonary embolism).
• Cardiology/ECG: AI-enabled ECG analysis and predictive analytics enable ambulatory monitoring and earlier intervention.
• Chronic-disease monitoring: SaMD platforms are embedded into remote patient monitoring workflows (diabetes, COPD, heart failure) enabling continuous data, predictive alerts and reduced readmissions.
• Operational workflows: SaaS-based software helps hospitals automate image-routing, triage, reporting, and integrates with EMRs/EHRs.

Strategic implications

• Companies that own the data pipeline (wearables, monitors, imaging archives) and can integrate AI/ML models stand to win.
• Successful SaMD vendors must not only build algorithms but also demonstrate clinical evidence, data robustness, algorithm governance and post-market monitoring.
• For CXOs: In 2025 you should ask: “Does our SaMD solution truly use AI/ML? Are we locked-algorithm only? Do we have lifecycle update controls and real-world monitoring?”

Digital Health & Remote Care — SaMD’s New Frontier

Transforming care delivery

• The global shift to value-based care, remote patient monitoring (RPM) and telehealth has created a demand for software-first medical solutions rather than hardware-only devices.
• SaMD is ideally positioned for this because it can operate across devices, integrate with cloud/data platforms, deliver analytics and adapt remotely.

Key trends for 2025

• More hospitals and health systems embracing home-based monitoring, requiring validated software to analyse patient-generated data and send real-time alerts to providers.
• Insurance and reimbursement models now favour tools that improve outcomes (reduced readmissions, fewer emergency visits) — positioning SaMD as outcome enablers rather than cost centres.
• Geographic growth: Emerging markets (India, China, Latin America) are quickly adopting digital health infrastructure; SaMD can leap-frog legacy hardware models and scale faster.

Why this matters

• If your product only addresses in-hospital use, you may be missing the fastest growing segment: home, outpatient, chronic-care.
• Decision-makers (CEOs, CISOs, CMIOs) should evaluate: “Is our software capable of remote deployment, connectivity, cloud analytics, and outcome-tracking?”
• Business models shift: SaMD is increasingly subscription-based (software-as-a-service), license + updates, or outcome-based (shared savings, pay-per-use) rather than one-time hardware sale.

Strategic Priorities for Market Leaders & Challengers

For market-leaders (large MedTech, enterprise software)

• Expand software portfolios from adjunct to stand-alone: convert hardware-dependent modules into SaaS/AI-enabled platforms.
• Acquire or partner with SaMD pure-play players (e.g., imaging-AI startups) to accelerate pipeline.
• Advocate regulatory readiness: ensure update-mechanisms, real-world data monitoring, transparency frameworks are in place.

For challengers / startups

• Focus on narrow clinical niches where AI/ML can deliver measurable value (e.g., stroke triage, echocardiography AI, home-monitoring analytics).
• Build fortes in data capture, algorithm validation, evidence generation.
• Align business models with payers and health systems: emphasise outcomes, ROI and integration.
• Ensure regulatory strategy is baked in early — lifecycle monitoring, AI change control, global harmonisation matter.

As we move through 2025, the SaMD landscape will continue to evolve rapidly:

• With over 1,000 AI/ML-enabled medical device authorisations in FDA records, the acceleration is unmistakable.
• Software-first healthcare strategies will become table stakes — if your organisation isn’t investing in SaMD, your hardware may become commoditised.
• For lead generation, you should position your market-research report or consult-ing offering to address: “Which SaMD niches will scale fastest? What regulatory pathways matter? How will business models shift?”
• CTA at end: invite decision-makers to book analyst calls, download sample chapters, or benchmark their software strategy against competitors.

Software as a Medical Device (SaMD) is no longer optional — it is fundamental to the future of healthcare delivery. Artificial intelligence and machine learning are accelerating capabilities; regulatory frameworks are aligning; and digital health + remote care models are creating new value and business models.

For CXOs, directors and decision-makers, 2025 is the year to ask: “Are we ready?”. The firms that act now will shape the next era of medical-software innovation.