SciMed Medical AI Governance

AI COMPLIANCE ASSESSMENT

Understand whether your AI-enabled medical device is prepared for emerging regulatory expectations

Need an independent view of your AI governance, validation, and documentation readiness before scrutiny increases?

Reserve Your Compliance Assessment

£4,950 | Fixed-scope assessment | Structured findings and prioritised roadmap delivered within 10 working days

Not sure yet? Book a free 30-minute Consultation →

A structured review of your AI governance, validation, documentation, and lifecycle readiness

The AI Compliance Assessment is a structured review of governance arrangements, validation approaches, technical documentation, and lifecycle controls for AI-enabled medical devices and IVDs.

It is designed for manufacturers who are:

  • Developing AI-enabled products

  • Preparing technical documentation

  • Assessing AI Act implications

  • Planning future market access activities

  • Reviewing existing AI-enabled products already on the market

  • Seeking greater confidence in their AI governance approach

We assess your current position across seven review dimensions, identify potential gaps, and provide a prioritised roadmap to support future compliance activities.

The objective is not simply to interpret regulations.

It is to help you understand whether governance, evidence generation, documentation, and monitoring activities are developing at the same pace as the technology itself.

Trusted by

[Bray Group]
[Caristo Diagnostics]
[C the Signs]
[CooperVision Specialty EyeCare]
[Innovia Medical]
[LifeScan]

What This Service Delivers

  • AI Governance Review

    • Assessment of ownership, accountability, decision-making structures, and governance maturity.

  • Regulatory Positioning Assessment

    • Review of AI-specific regulatory considerations, obligations, and areas likely to attract future scrutiny.

  • Validation & Evidence Review

    • Assessment of how AI performance is validated, justified, and aligned to intended use.

  • Documentation Readiness Review

    • Evaluation of technical documentation maturity, traceability, and AI-specific evidence.

  • Lifecycle & Monitoring Assessment

    • Review of post-market monitoring, performance oversight, change control, and lifecycle management arrangements.

  • Gap & Risk Summary

    • Clear identification of areas requiring further consideration, together with likely impact and priority.

A structured review of your AI readiness, with prioritised recommendations and practical next steps

The assessment is designed to help manufacturers understand where existing systems already provide a strong foundation and where targeted improvements may be beneficial.

What You Will Receive

  • AI Compliance Assessment Report

  • Findings across seven review dimensions

  • Gap and risk summary

  • Prioritised action roadmap

  • Executive briefing session

  • Opportunity to discuss findings with a SciMed consultant

Typical Inputs

The assessment is tailored to your product, development stage, and current documentation maturity.

Depending on the nature of the product, inputs may include:

  • Intended use and product overview

  • Existing technical documentation

  • Validation and performance evidence

  • Risk management documentation

  • Governance procedures and responsibilities

  • Post-market monitoring information (where applicable)

The assessment is intended to provide clarity, direction, and confidence before governance, validation, or documentation challenges become more difficult to address, and all information is reviewed under NDA.

SciMed consultant reviewing clinical evaluation documentation as part of a gap analysis assessment

The Seven Review Dimensions

1) Applicability & Regulatory Positioning

Does the AI functionality create obligations that have not yet been fully considered?

We review:

  • The role of AI within the product

  • Interaction between MDR/IVDR and AI-related requirements

  • Product claims and intended use

  • Areas likely to attract future regulatory scrutiny

  • Existing assumptions regarding AI compliance

The objective is not to determine legal classification.

It is to identify where regulatory positioning may require further review.

2) Governance & Accountability

Are AI-related decisions owned, documented, and appropriately governed?

We review:

  • Governance structures

  • Accountability and ownership

  • Decision-making processes

  • Cross-functional responsibilities

  • Escalation and oversight arrangements

Many organisations already possess the necessary expertise. The challenge is often demonstrating how key decisions are made, reviewed, and controlled.

3) Validation & Evidence

Can confidence in AI performance be clearly justified?

We review:

  • Validation approaches

  • Performance justification

  • Alignment with intended use

  • Evidence generation strategies

  • Documentation supporting performance claims

The focus is not simply whether validation exists, but whether the rationale behind it is defensible.

4) Human Oversight & Risk Management

Are AI-specific risks appropriately identified, controlled, and monitored?

We review:

  • Risk management activities

  • Human oversight arrangements

  • User interaction assumptions

  • Reliance and misuse considerations

  • Monitoring of AI-related risks

Particular attention is given to how users interact with AI outputs and how limitations are communicated.

5) Technical Documentation Readiness

Does documentation clearly explain how confidence in the AI system is established and maintained?

We review:

  • Technical documentation maturity

  • Traceability of key decisions

  • AI-specific evidence

  • Documentation coherence

  • Alignment across supporting records

The objective is to determine whether documentation tells a clear and defensible story.

6) Post-Market Monitoring & Lifecycle Management

Are systems in place to support ongoing confidence in the AI system after deployment?

We review:

  • Monitoring strategies

  • Performance oversight

  • Feedback mechanisms

  • Trend review processes

  • Lifecycle controls

This includes consideration of how future issues would be identified, investigated, and addressed.

7) Change Control & Future Readiness

Is the organisation prepared to manage future changes to the AI system?

We review:

  • Change control processes

  • Update governance

  • Retraining considerations

  • Future modification planning

  • Long-term readiness

The focus is on ensuring that future changes can be evaluated, documented, and controlled in a structured and defensible manner.

Additional Deliverables

  • Prioritised Action Roadmap

    • A practical summary of recommended next steps, prioritised according to likely impact and urgency.

  • Gap & Risk Summary

    • Identification of key observations across governance, validation, documentation, and lifecycle management activities.

  • Immediate Priorities vs Longer-Term Actions

    • Clear distinction between issues that may require near-term attention and those better addressed through longer-term planning.

  • Executive Briefing

    • A 30-minute walkthrough of findings, observations, and recommended next steps with a SciMed consultant.

Want an independent view of your AI governance readiness?

Reserve Your AI Compliance Assessment

Fixed fee £4,950. Delivered in ten working days. NDA in place before document sharing.

Fixed-scope assessment with structured findings and prioritised recommendations.

Not Ready Yet? Start with our AI Act x MDR/IVDR Compliance Crosswalk

Use our EU AI Act x MDR/IVDR Compliance Crosswalk to understand where the requirements overlap, common gaps emerge, and how to avoid creating regulatory debt.

Why Early AI Governance Review Matters

The pattern is becoming increasingly familiar. An organisation develops or acquires an AI-enabled product, establishes a validation approach, generates supporting evidence, and builds technical documentation around the intended use. The product may even be successfully placed on the market. The challenge often emerges later.

In many cases, the issue is not the technology itself. It is the accumulation of what we describe as regulatory debt: governance, validation, documentation, and lifecycle decisions that were never fully documented or justified because they did not appear critical at the time.

As AI governance expectations mature and regulatory scrutiny increases, organisations are required to explain not only what the AI system does, but also:

  • How confidence in performance was established

  • How limitations were identified and communicated

  • How risks were evaluated and controlled

  • How oversight responsibilities were defined

  • How ongoing performance will be monitored

Many manufacturers already possess substantial documentation and evidence. However, they sometimes discover that important governance, validation, or lifecycle decisions were never fully documented at the time they were made, creating significant remediation effort later, and the impact is often wider than the issue itself.

Potential consequences may include:

  • Additional documentation work,

  • Delays to regulatory activites,

  • Increased remediation costs,

  • Reduced confidence during audits, and

  • Internal pressure on development, regulatory, and commercial timelines.

In many cases, these issues could have been identified much earlier through a structured review of governance, validation, documentation, and lifecycle management activities. The purpose of the AI Compliance Assessment is not to create additional work. It is to help manufacturers identify where existing systems already provide a strong foundation, where targeted improvements may be beneficial, and where future compliance challenges may be developing.

How SciMed Supports AI Readiness

We review your current position using the same practical, evidence-based approach that underpins our broader regulatory and clinical evaluation work.

Our objective is to identify and prioritise issues before they become more difficult, costly, or disruptive to address.

Our Approach:

  • Information Review

    • Relevant governance documentation, validation evidence, technical documentation, procedures, and supporting materials are shared under NDA.

  • Structured Assessment

    • Review against the seven assessment dimensions, with consideration of current regulatory expectations and emerging AI governance requirements.

  • Gap & Risk Evaluation

    • Identification of areas requiring further review, clarification, strengthening, or future planning.

  • Readiness Assessment

    • Evaluation of organisational readiness across governance, validation, documentation, monitoring, and lifecycle management activities.

    Report Delivery

    • Structured written findings, prioritised recommendations, and roadmap for future action.

    Executive Briefing

    • 30-minute walkthrough of findings, observations, and recommended next steps with a SciMed consultant.

    Optional Implementation Support

    • Where appropriate, SciMed can provide follow-on support for governance development, documentation, validation strategy, remediation activities, and market access preparation.

Why Companies use SciMed for AI Compliance Assessments

  • Governance Responsibility

    • …is not formally assigned or documented

  • Validation Approaches

    • …are difficult to justify retrospectively

  • Human Oversight Assumptions

    • …are understood internally but not explicitly described

  • Monitoring Activities

    • …do not address AI-specific performance considerations

  • Technical Documentation

    • …lacks traceability between key decisions, supporting evidence, and product claims

  • Change Control Processes

    • …do not fully address future AI updates or modifications

  • Cross-Functional Responsibilities

    • …are understood informally but not clearly defined

Every organisation starts from a different position.

Some manufacturers are assessing AI governance requirements during early development. Others are reviewing products that are already on the market. Many are trying to understand how existing MDR or IVDR compliance activities interact with emerging AI-related expectations.

While the specifics vary, assessments frequently identify themes such as:

These observations do not automatically indicate non-compliance, in fact, in many cases, organisations already possess strong foundations in quality management, risk management, validation, technical documentation, and post-market activities.

The challenge is often determining whether those existing systems adequately address AI-specific governance, oversight, documentation, and lifecycle considerations. Identifying these issues early allows manufacturers to prioritise activities, allocate resources appropriately, and strengthen confidence in their future regulatory position before scrutiny increases.

Why Companies Use SciMed

MedTech Regulatory Expertise

Our team works exclusively within highly regulated health technology environments, supporting manufacturers across clinical evaluation, performance evaluation, post-market activities, regulatory strategy, and market access.

AI governance is not treated as a standalone discipline. It is assessed within the wider context of product safety, performance, evidence generation, and regulatory expectations.

Practical, Not Theoretical

The objective is not to produce a lengthy list of possible obligations. It is to identify the specific governance, validation, documentation, and lifecycle considerations most relevant to your product and development stage.

Our recommendations are designed to support decision-making, prioritisation, and practical implementation.

Focused On Future Readiness

Many organisations are still determining how AI governance expectations will affect their products.

The assessment is designed to help manufacturers understand where existing systems already provide a strong foundation and where future scrutiny may require additional evidence, controls, or documentation.

Independent Perspective

Internal teams are often closely involved in development decisions and day-to-day project activities.

An independent assessment can provide valuable perspective on assumptions, risks, dependencies, and areas that may benefit from further review.

Proportionate Recommendations

Not every observation requires immediate action, not every gap requires a major remediation programme.

Our focus is on helping manufacturers distinguish between:

  • Immediate priorities

  • Medium-term improvements

  • Longer-term governance considerations

so resources can be allocated appropriately.

Reserve Your AI Compliance Assessment

Reserve Your AI Compliance Assessment

Or book a free 30-minute Consultation →

If you are developing an AI-enabled medical device or IVD, preparing technical documentation, assessing AI Act implications, or reviewing an existing product against emerging expectations, the AI Compliance Assessment provides a structured way to understand your current position.

The Assessment Includes

✓ Structured review across seven assessment dimensions

✓ Governance and accountability assessment

✓ Validation and evidence review

✓ Documentation readiness assessment

✓ Monitoring and lifecycle review

✓ Gap and risk summary

✓ Prioritised action roadmap

✓ Executive briefing with a SciMed consultant

Not ready to reserve yet?

If you'd like to talk through your situation before committing, book a free 30-minute Gap Analysis Consultation. We'll look at your current position and tell you honestly whether the Gap Analysis is the right next step.

Book a Consultation →

Not Ready for an Assessment Yet?

If you are still exploring how MDR, IVDR, and the EU AI Act interact, our practical Compliance Crosswalk and Medical AI Governance Scorecard provide a useful starting point.

EU AI Act × MDR/IVDR Compliance Crosswalk

Understand where requirements overlap, where gaps commonly emerge, and how to avoid creating unnecessary remediation effort later.

A practical guide for manufacturers of AI-enabled medical devices and IVDs.

Medical AI Governance Scorecard

Benchmark your readiness across governance, validation, documentation, change control, and post-market monitoring activities. Together, these resources help manufacturers understand where AI governance considerations may already be influencing regulatory readiness and where further review may be beneficial.