Can AI Be Classed As A Medical Device?

A 2026 Perspective From The ZES Experts

Introduction: The Client Enquiry

Recently ZES were contacted by a Client who were seeking expert answers and regulatory guidance to their question "Can Artificial Intelligence (AI) be classed as a Medical Device?" This is a rapidly evolving and increasingly complex topic in 2026 and ZES place themselves at the forefront of developments.

In 2026, AI continues to transform the Healthcare landscape, from diagnostic support tools and predictive analytics to automated image interpretation and Clinical decision support systems, Life Science organisations are facing important questions about classification, compliance, and regulatory responsibility.

Determining whether an AI-based system qualifies as a Medical Device is not always straightforward. The answer depends on factors such as intended use, functionality, level of autonomy, and the claims made by the manufacturer.

With Regulators worldwide placing greater scrutiny on software and AI-driven technologies in Healthcare, understanding where a product sits within the Regulatory Requirements is critical. Misclassification can result in significant compliance risks, delays to market, or enforcement action.

This Client’s question reflects a wider industry challenge, in which ZES play a pivotal role. ZES help Clients to navigate the intersection of innovation and Regulation in a way that ensures both Patient safety and commercial success.

In this blog, ZES explore when AI may be considered a Medical Device, ZES highlight the key Regulatory principles involved, and what Life Science organisations should consider when developing or deploying AI-driven Healthcare solutions.

Redefining What Medical Devices Can Do

AI is transforming virtually every industry, but perhaps nowhere is its impact more profound than in Healthcare. From predicting disease progression to interpreting radiological images, AI-powered systems are reshaping Clinical decision-making and ultimately the standard of Patient Care.

However, as AI-powered systems and technologies advance, in the opinion of ZES, a key regulatory question emerges: "Can AI be classed as a Medical Device?" Understanding this is crucial for Developers, Manufacturers, Regulators, and Healthcare providers alike, particularly as the legal landscape evolves, certainly in the developed world.

One company helping Life Science organisations navigate this complexity is ZES. Known for providing GxP Engineering, IT Consultancy, and Validation services (amongst others) to Pharmaceutical and Medical Device manufacturers, ZES support Client Medical Device compliance with Regulatory Requirements including those covering AI and Software related products.

What Is A Medical Device? The Regulatory Baseline

Before a decision can be made as to whether an AI-powered system can be classed as a Medical Device, in the first instance, an understanding of what Regulators actually mean by the term "Medical Device" as defined in their Regulatory Requirements, must be understood.

In the most established Regulatory Requirements, such as those used by the UK’s Medicines and Healthcare products Regulatory Agency (MHRA), the US Food and Drug Administration (FDA), and the European Medical Device Regulation (MDR), a Medical Device is defined by its intended purpose rather than by its driving technology or form. Therefore it can be concluded that a product is a Medical Device if it is intended to help a Patient by:

• Diagnosing, preventing, monitoring, or treating disease
• Affecting the structure or function of the Patient's body
• Providing accurate information to Medical Practitioners to enable medical decisions to be made about a Patient's well-being.

The above baseline functional definition means that Medical Devices may be physical instruments (like a stethoscope), software programs, or even algorithms, as long as their intended use meets the criteria as set out above.

Critically, this applies regardless of whether the Medical Device is Hardware, Software, or a combination of both. Standalone Software developed for medical purposes, including those utilising AI, in the opinion of ZES, generally qualify as a Medical Device if it performs functions that would subsequently require Clinical judgment about a Patient.

AI And Software As A Medical Device (SaMD)

In recent years, ZES have seen Regulators increasingly categorise AI that meets the Medical Device definition as either Software in a Medical Device (SiMD) or Software as a Medical Device (SaMD).

• Software in a Medical Device (SiMD): Software that is part of a physical Medical Device and essential to its function (e.g., AI code embedded in an imaging machine)
• Software as a Medical Device (SaMD): Software that functions independently of Hardware and can fulfil a Medical purpose on its own (e.g. an AI tool that analyses Patient data to estimate disease risk)

Under both definitions, in the opinion of ZES, what matters most is "Intended Use". AI systems that analyse Clinical Data, influence diagnoses, or recommend treatment decisions fall within Medical Device regulations, and therefore must comply with the same safety, performance, and Quality standards as a traditional Medical Device.

Why AI Is A Medical Device

When and why is AI classed as a Medical Device? In the opinion of ZES, the answer ultimately depends on the breadth and extent of the Medical Device's capabilities. Or in other words, how far the Medical Device's functionality extends and the range of functions it is designed to perform. This is explored further below:

1. AI For Diagnosis Or Clinical Decision Support

AI that directly aids diagnosis, triages conditions, or provides therapeutic recommendations usually triggers a Medical Device class status. For example:

• An AI tool that detects diabetic retinopathy in retinal scans
• An algorithm that predicts risk of heart attack from Clinical Data
• A machine learning model recommending treatment strategies

These software systems influence Clinical decisions directly — and Regulators globally are clear that this purpose brings them under their Medical Device Regulatory Requirements.

In many cases, Medical Device manufacturers of such devices must demonstrate safety and performance through rigorous Validation and Regulatory submissions before the Medical Device product can be marketed in a particular country. This is where specialist Consultants from ZES provide Clients with invaluable support. For instance, ZES offer Regulatory, IT and Engineering support to help Medical Device manufacturers achieve FDA 510(k) clearance for AI and SaMD products, addressing challenges like Software Validation and Risk Management.

2. AI Embedded In Medical Devices

AI can also be an integrated component of a larger Medical Device. For example, an AI algorithm might power the imaging analysis of an MRI scanner or enhance the signal processing of a heart monitor. In such cases, the AI is part of a Regulated Medical Device and must meet the same Quality and compliance expectations of the associated Regulatory Authority.

ZES support Clients to ensure that these integrated AI systems meet GxP (Good Practice) IT, Engineering and Validation compliance, by ensuring Medical Devices comply with the Regulatory Requirements for Safety and Effectiveness. 

3. AI Tools With Ambiguous Clinical Roles

In the opinion of ZES, not all AI systems are Medical Devices. For example, AI used solely for administrative tasks (e.g., scheduling appointments, workflow management) typically falls outside the Medical Device regulations. The key distinction is whether the system's AI directly contributes to Clinical decisions or Patient outcomes.

Regulators also consider whether Healthcare professionals can independently review the underlying rationale of the system’s output. If not, the system is more likely to be regulated as a Medical Device.

In all cases, ZES support Clients with Inspection Readiness and suitable technical documentation.

Regulatory Challenges Specific To AI

Whilst the principles of defining a system as a Medical Device as set out above may seem relatively straightforward, in the experience of ZES, there are unique challenges when applying them to AI systems. These include:

• Adaptive Learning: Some AI systems evolve over time through Machine Learning, which raises questions about ongoing Validation and Performance Monitoring
• Explainability: Regulators are increasingly focused on whether developers can explain how an AI system reaches its conclusions
• Dataset Bias: AI systems trained on unrepresentative Data can unfairly disadvantage certain Patient groups. In the experience of ZES, this is a real risk, that Regulators require to be addressed through robust Validation and Risk Management.

These challenges complicate Compliance and highlight the reasons why subject matter experts, such as ZES, who offer GxP Engineering and IT Consultancy services designed to help Life Science organisations, implement robust Validation processes, manage Risks, and prepare Regulatory Submissions. All of these are essential when AI is or might be classed as a Medical Device.

The Future Of AI In Medical Devices

Government Legislators and their associated Regulators from around the world are updating their Regulatory Requirements to better accommodate the new age of AI. For example:

• The FDA have developed and, in Jan 2025, issued Draft guidance entitled "Artificial Intelligence-Enabled Device Software Functions: Lifecycle Management and Marketing Submission Recommendations"
• The MHRA have issued guidance on their website with an umbrella webpage entitled “Software and artificial intelligence (AI) as a medical device.” Various guidance documents can be accessed regarding Medical Devices and the Regulatory Expectations of AI in a Medical Device.
• The EU, via MDR and supplemental guidance issued in June 2025, treats AI Software within the same Risk-Based framework as other Medical Devices.
  

These developments reflect an ongoing recognition that AI does not exist outside Healthcare Regulation simply because it is Software Code. The impact on Patient Safety determines whether the AI should be treated as a Medical Device.

Final Thoughts

In the opinion of ZES, in 2026, given the recently Regulatory issued guidance, AI can absolutely be classed as a Medical Device — but only when its intended use directly relates to Patient Care, Diagnosis, Monitoring, Treatment, or other Clinical Decision Support.

In defining whether a system utilising software in whole or in part, is a Medical Device, various Regulators from around the world have moved toward a technology-neutral, Risk-Based Approach, focusing on whether a system's use affects Patient Health Outcomes rather than what the system is technically.

In the opinion of ZES, Life Science organisations who are developing AI in Healthcare must therefore ask themselves the following: Does our AI system influence Clinical decisions or outcomes? If the real answer is "Yes", ZES therefore recommend that the AI system falls under the associated Medical Device regulations depending on where the Medical Device is to be utilised. Compliance IS NOT an option.

Zener Engineering Services Ltd help Life Science organisations navigate these complex Regulatory Requirements, providing GxP Validation Services, Engineering and IT support, Inspection Readiness, and strategic Regulatory guidance. This applies especially to AI and SaMD products intended for use in highly regulated markets such as the UK, EU, and US.

Whether you're a Life Science organisation innovating and building new AI systems or a Regulator updating compliance Regulatory Requirements, in the opinion of ZES, the underlying reality remains: Intention and Patient Impact define whether AI is a Medical Device, where a robust Validation exercise, Governance programme, and Risk Management will ensure the AI Medical Device will deliver safe and effective Healthcare outcomes.

Contact ZES For All Your GxP AI Medical Device Solutions