DR. JOHN VOURGANAS
MSc · PhD · CEng
AI Governance
Executive
AI systems in regulated environments don't fail because the technology is wrong.
EU AI ACT
revFADP
I design that layer. Then I build what sits beneath it.
NIS2
ISO 42001
Where I Operate
I work at the level where AI strategy, regulatory accountability, and system architecture converge, in environments where the cost of getting it wrong is high.
My work covers four domains:
AI governance frameworks built for accountability, defensibility, and regulatory scrutiny, not compliance theatre
Risk architecture and model governance embedded as structural system properties, from design through to live deployment
Regulatory alignment across EU AI Act, GDPR, NIS2, ISO 42001, and Swiss revFADP, translated into operating models boards can stand behind
Executive advisory for CEOs, CTOs, and CROs navigating consequential AI adoption decisions in regulated environments
Dr. Vourganas
AI systems in regulated environments don't fail because the technology is wrong. They fail because the decision space was never explicitly designed.
I design that layer. Then I build what sits beneath it.
For over a decade I have operated at executive level in environments where AI governance failure means regulatory action, financial liability, clinical harm, or infrastructure exposure, holding accountability from board conversation to system architecture, across cybersecurity, financial services, digital health, and critical infrastructure.
I work with organisations across Swiss, UK, and EU markets, and directly with CEOs, CTOs, and CROs who need a thinking partner who holds the technical depth, the regulatory accountability, and the executive perspective simultaneously.
Where I Have Operated
Cybersecurity & Critical Infrastructure
AI systems in national security and critical infrastructure environments fail when decision processes lack transparency and human oversight. I have designed governance architectures for explainable threat detection, responsible automation, and resilient AI deployment in environments where operational failure has institutional and national consequences.
Digital Health
Clinical AI operates under strict safety, liability, and regulatory constraints. As CTO of a regulated digital health platform, I led AI development and governance under GDPR, MHRA, and NHS clinical safety frameworks, taking the system from concept to regulated pilot deployment in live patient care environments.
Financial Services
AI systems in regulated financial environments must withstand supervisory scrutiny, model risk review, and audit traceability. I design governance and explainability frameworks ensuring documented model accountability, regulatory alignment, and audit-ready lifecycle governance from design to deployment.
Does Your AI System Pass Governance Scrutiny?
Most organisations find out their governance has gaps at the worst possible moment, during regulatory review, audit, or after a deployment failure.
This executive assessment evaluates your AI system's readiness across four structural dimensions, producing a deployment determination and executive action plan aligned with EU AI Act, ISO/IEC 42001, and Swiss revFADP.
No registration. No consultation required. Run it now.
Applications of Machine Learning in Cyber Security: A Review
Journal of Cybersecurity and Privacy (MDPI), 2024
A structured review of ML and AI in cybersecurity, examining real-world applicability gaps and their implications for trustworthy, auditable AI governance.
Responsible AI for Home-Based Rehabilitation
Sensors (MDPI), 2021
An ethical AI framework for home-based rehabilitation, introducing a hybrid machine learning model demonstrating governance-by-design in regulated clinical environments.