Fifteen-plus years across risk, compliance, governance, ethics, and legal. The judgment that only comes from sitting in the chair.
Andrea Elliott founded EMG Advisory in February 2026 to address a gap she witnessed firsthand: the disconnect between where AI actually is inside organizations today and where the world assumes it should be. Most enterprises are still building the infrastructure to get the highest value out of AI. EMG exists to help them build it.
With 15+ years across risk, compliance, governance, ethics, and legal, Andrea most recently served as Chief Compliance Officer at a publicly traded payments technology company. In that role, she led a global risk and compliance transformation, overseeing enterprise risk management, regulatory compliance, AI governance, data privacy, business continuity, third-party risk, industry scheme compliance (e.g., PCI, ISO, etc.), and client assurance. She built and implemented the company's AI governance framework, embedding responsible and regulatory-compliant AI practices across the enterprise.
She founded EMG to fill what she calls "the missing middle": the operational infrastructure that ensures enterprise AI use aligns with organizational strategy, values, and regulatory obligations. Her commentary, "The Missing Middle" (April 2026), has helped shape the conversation about how organizations bridge AI principle to practice.
Most enterprises treat AI governance as a tax on innovation. That framing is wrong. Companies that build the operational layer now do not just manage risk. They unlock the ability to do more with AI, faster, with the credibility to shape the regulatory environment rather than react to it.
The conversation is happening at two altitudes that don't connect. At the top, frontier labs debate superintelligence. On the ground, enterprises are still answering fundamental questions about what AI they run and who owns it. The work that closes that gap is operational, and it is the responsibility of leadership.
The level of rigor an organization applies to AI risk management should be proportionate to the risks created by its activities and the role it plays in the value chain. Not all AI use cases require the same level of oversight. Internal tools get a fast lane. High-stakes AI gets rigorous controls. Frameworks must be right-sized.
AI governance fails when it lives off to the side. The work it touches, risk, compliance, security, privacy, legal, procurement, is already in motion across the enterprise. Whether AI oversight is structured through a dedicated committee, embedded inside existing forums, or a hybrid, the standard is the same: one coherent governance system, not a parallel one.
Every engagement starts with a conversation. No commitment, no cost. Share where you are, and Andrea will share where the highest-leverage starting point is.
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