Bridging quality systems, regulatory affairs, and legal expertise to help regulated organizations build AI governance programs that auditors respect and executives understand.
The Story
Most people entering the AI governance space come from cybersecurity, data science, or tech policy. Jared Clark took a different path — one that starts with quality systems, winds through regulatory affairs, and arrives at AI governance with a perspective that most practitioners in this space simply don't have.
The journey began in law. A Juris Doctor provides more than legal knowledge — it trains you to dissect regulatory language, identify compliance obligations, structure arguments that withstand scrutiny, and think about risk in terms of liability and exposure. These are exactly the skills needed when an organization asks, "What does the EU AI Act actually require us to do?"
From there, the path moved into quality management and organizational excellence. This is where the real foundation for AI governance was built. Quality management systems — ISO 9001, ISO 13485, GMP frameworks — are fundamentally about ensuring that processes are documented, controlled, monitored, and continuously improved. They require organizations to define policies, assign responsibilities, manage risk, maintain records, and submit to audits. If that sounds familiar, it should: AI governance frameworks like ISO 42001 are built on the same management system architecture.
Regulatory affairs came next. Working with the FDA, navigating EU MDR requirements, and managing the documentation and compliance obligations that regulated industries face every day. Regulatory affairs is the discipline of translating regulatory requirements into organizational action — and that translation capability is precisely what AI governance demands as the EU AI Act, FDA AI/ML guidance, and sector-specific AI regulations take effect.
This is a path that maps directly to what AI governance actually requires. Not cybersecurity architecture. Not machine learning model development. AI governance is about building management systems for responsible AI — policies, processes, risk frameworks, oversight structures, documentation, audits, and continuous improvement. It's quality management applied to artificial intelligence. And the people who have spent their careers building and auditing quality management systems are the people best equipped to build AI governance programs that work in practice, not just in theory.
After more than fifteen years in regulated industries — serving healthcare, pharmaceutical, manufacturing, and defense organizations — the convergence of AI and regulation made the next step clear. The organizations Jared had spent years helping with quality systems and regulatory compliance were now deploying AI systems that needed governance. The methodology was already there. It just needed to be applied to a new domain.
Credentials
Each credential represents a discipline that maps directly to AI governance requirements. Together, they form an expertise profile that is exceptionally rare in this emerging field — and precisely what regulated organizations need.
Regulatory Interpretation & Compliance Architecture
Legal training provides the foundational ability to interpret regulatory text with precision — a skill that becomes critical when organizations need to understand exactly what the EU AI Act, FDA AI/ML guidance, or sector-specific AI regulations require. The JD brings expertise in regulatory interpretation, compliance framework design, contract structures for governance engagements, liability analysis, and the ability to construct arguments that withstand regulatory scrutiny.
Why it matters for AI governance: When regulators write requirements like "appropriate levels of transparency" or "proportionate risk management measures," legal training is what determines whether your organization's interpretation will hold up under audit. Every governance policy, every risk assessment methodology, every compliance documentation structure benefits from the precision that legal training provides.
Strategy, Change Management & Executive Communication
AI governance doesn't exist in a vacuum — it operates within organizational structures, budgets, strategic priorities, and political dynamics. The MBA provides expertise in business strategy, organizational change management, stakeholder communication, and the executive-level framing needed to secure buy-in for governance programs that often lack an obvious ROI.
Why it matters for AI governance: The biggest barrier to effective AI governance is rarely technical. It's organizational. Getting boards to prioritize governance investment, convincing engineering teams to adopt new processes, and demonstrating business value to CFOs who see governance as cost — these are business challenges that require business training. A governance framework that's technically perfect but organizationally rejected is worthless.
Governance Implementations That Ship on Time
PMI-certified project management methodology ensures that governance implementations are scoped, planned, executed, and delivered with the same rigor applied to any critical business initiative. The PMP brings structured work breakdown, stakeholder management, risk management, schedule management, and the discipline to keep complex, multi-workstream governance programs on track.
Why it matters for AI governance: AI governance implementations fail more often from poor project management than from poor technical design. When an organization needs to be EU AI Act compliant by August 2, 2026, the governance framework needs to be implemented on a timeline — not in an open-ended advisory engagement that drifts past the deadline. The PMP ensures that governance programs have milestones, deliverables, and accountability structures that drive completion.
Quality Management Systems — The Backbone of AI Governance
The ASQ Certified Manager of Quality/Organizational Excellence certification represents mastery of the quality management discipline — process design, statistical thinking, continuous improvement, management system architecture, audit methodology, and organizational excellence frameworks. This is the credential that most directly maps to what AI governance actually is.
Why it matters for AI governance: ISO 42001, the international standard for AI management systems, is built on the same Annex SL management system architecture as ISO 9001, ISO 14001, and ISO 27001. If you've spent your career building, maintaining, and auditing management systems, you understand the architecture that AI governance requires — leadership commitment, planning, support structures, operational controls, performance evaluation, and continuous improvement. The CMQ-OE is the credential that proves you don't just understand AI governance theory; you know how to build management systems that pass third-party audits.
FDA, EU MDR, and Now EU AI Act — Regulatory Affairs Is the Bridge
The RAPS Regulatory Affairs Certification represents expertise in regulatory strategy, submission management, and compliance across international regulatory frameworks. Originally focused on medical devices and pharmaceuticals (FDA, EU MDR, Health Canada), the regulatory affairs discipline now extends directly into AI regulation as the EU AI Act introduces conformity assessment, technical documentation, and post-market surveillance requirements that mirror the regulatory frameworks medical device and pharma companies already know.
Why it matters for AI governance: The EU AI Act's high-risk AI requirements — conformity assessments, technical documentation, quality management systems, risk management, and post-market monitoring — are structurally identical to the requirements in EU MDR and FDA 21 CFR Part 820. Organizations that already operate under these medical device regulations have a compliance infrastructure that can be extended to AI governance. A RAC-certified consultant understands both sides of this bridge and can help organizations leverage their existing regulatory capabilities for AI compliance.
The Approach
The approach at Regulated AI Consulting starts from a simple premise: AI governance is a quality management challenge. The same disciplines that organizations use to manage product quality, process control, and regulatory compliance are the disciplines needed to govern AI systems responsibly.
This means AI governance programs should integrate with existing quality management systems, not create parallel bureaucracies that duplicate effort and confuse accountability. An organization with a mature ISO 9001 QMS already has the infrastructure for leadership commitment, documented processes, risk-based thinking, internal audits, and management review. Extending that infrastructure to cover AI systems is faster, cheaper, and more sustainable than building a separate governance structure from scratch.
Every engagement is built on this principle of integration. Whether it's an AI risk assessment, ISO 42001 implementation, or EU AI Act compliance program, the deliverables are designed to work within the management systems and organizational structures that already exist. The goal is practical governance that auditors will accept and operational teams will actually follow — not theoretical frameworks that look good in a boardroom presentation but fail under real-world scrutiny.
AI governance programs build on existing QMS infrastructure rather than creating parallel systems that drain resources and fragment accountability.
Every framework, policy, and procedure is designed to withstand third-party audit scrutiny — because governance that can't survive an audit isn't governance.
You work directly with Jared Clark — the person with the credentials, the experience, and the accountability. No bait-and-switch staffing.
Deliverables are operational tools your teams will use daily — not academic papers that collect dust. Every framework comes with implementation guidance.
Governance programs include monitoring, measurement, and improvement mechanisms — because AI risk evolves, and governance must evolve with it.
The Firm
Regulated AI Consulting is an AI governance advisory practice operated by Certify Consulting LLC. It exists to serve a specific need: helping regulated organizations build defensible, practical AI governance programs that integrate with their existing management systems and satisfy the regulatory frameworks that matter most — ISO 42001, the EU AI Act, FDA AI/ML guidance, and NIST AI RMF.
Regulated AI Consulting is part of a constellation of specialized practices under Certify Consulting. Certify Consulting provides traditional certification consulting for organizations pursuing ISO 9001, ISO 13485, ISO 27001, and other management system certifications. ISO42001Consultant.com serves as a deep-dive educational resource for organizations evaluating ISO 42001 specifically.
This structure reflects a deliberate philosophy: specialized expertise delivered through focused practices, each with its own depth and identity, but all backed by the same advisory firm and the same practitioner. When you engage Regulated AI Consulting for AI governance, you're working with an advisor who also understands the broader quality and regulatory landscape — because AI governance doesn't exist in isolation from the management systems it integrates with.
ISO certification consulting for quality management systems, medical devices, information security, and environmental management.
certify.consultingIn-depth resource for ISO 42001 — the international standard for AI management systems. Implementation guides, gap analysis tools, and expert guidance.
iso42001consultant.comStart with a free 30-minute consultation. We'll discuss your organization's AI landscape, regulatory exposure, and what a governance program looks like for your specific situation. No sales pitch — just a candid assessment of where you stand and what comes next.
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