🎯 What Every AI Healthtech Startup Misses About Compliance — Until It’s Too Late
If you're developing an AI product for healthcare in the UK or EU, your biggest risk isn’t technical.
It’s regulatory readiness — and the assumptions you're making about it.
After working with dozens of AI health startups, here are 3 things most teams get wrong (all covered in our Regulatory Readiness Toolkit):
1. MHRA Software Classification Isn’t Just a Checkbox
If your AI tool influences clinical decision-making (even as a recommender), it likely qualifies as a Class IIa or higher medical device under Rule 11. That means you’ll need Notified Body engagement, a technical file, and CE/UKCA marking — not just a pilot and good intentions.
📌 Takeaway: If you haven’t defined your intended use precisely, you're already behind.
2. NICE Doesn’t Just Want "Evidence" — They Want Specific Types of Evidence
Under Tier C of the NICE Evidence Standards Framework (ESF), you need to show:
Performance in an NHS-relevant setting
Evidence of clinical safety and effectiveness
A clear plan for post-market monitoring
📌 Takeaway: Academic papers won’t cut it — you’ll need real-world validation, and it must be structured around ESF Standards 14–16.
3. The EU AI Act Applies to You — Even Before Enforcement Begins
The EU AI Act is already in force (Regulation 2024/1689), and while enforcement ramps up in 2026, it already defines most health AI as “high-risk”. That brings obligations like:
Risk management documentation
Bias mitigation strategies
Human oversight safeguards
A technical annex (Annex IV) specific to AI
📌 Takeaway: Being “GDPR-compliant” ≠ being AI Act–ready.
The Toolkit That Helps You Fix All of This
We’ve condensed all of these frameworks — MHRA, GDPR, NICE, NHS AI Hub, and the EU AI Act — into a single audit toolkit, designed for AI health teams.
It’s not free — it’s £1,150 — but it gives you what a regulatory consultant would build over several weeks. And it’s built for you to run, adapt, and own.
