After years implementing data and analytics solutions at enterprise scale, I watched organizations rush AI deployment without governance frameworks. The result? Regulatory risk, talent attrition, and boardroom exposure that could have been prevented.
Now I work with executive leadership—GCs, CIOs, Chief AI Officers—to build governance that actually holds up under pressure and audit.
AIML Governance LLC helps you deploy AI with confidence.
I started my career as a data and analytics leader in heavily regulated industries. At McKesson, I managed data pipelines that fed everything from device safety analytics to pharmaceutical forecasting. Every decision had real consequence: a misaligned model could delay a drug approval or mask a safety signal. That accountability shaped how I think about technology governance.
Later, at Meta, I worked at the intersection of product scale and governance—seeing firsthand how organizations that bake accountability into their systems early avoid catastrophic missteps. I watched peers at the Harvard Kennedy School build public policy on top of evidence-based frameworks. I realized: governance isn’t a compliance burden. It’s strategic infrastructure.
The turning point came when I kept encountering the same pattern: executives deploying AI without a governance playbook, then scrambling when regulators called, boards asked hard questions, or teams started leaving because ethical concerns weren’t taken seriously. I decided to stop advising from the sidelines and build a firm that helps leaders prevent that situation entirely.
Governance isn’t a box to check. It’s a leadership competency—the same way financial controls, information security, and talent strategy are. The best governance is invisible because it’s embedded into how your organization makes decisions about AI. It shows up in hiring, in architecture reviews, in board reporting, in how you handle model failures.
Most organizations approach governance backward. They wait for a problem—bias in hiring, regulatory pressure, a public failure—then scramble to retrofit controls. By then, the damage is done. I work with teams that want to be proactive: building governance that creates competitive advantage, not just compliance theater.
That’s why I focus on higher education and regulated industries. In those sectors, governance directly impacts your license to operate. A university managing student data, a pharma company deploying algorithms in clinical workflows, a financial services firm managing inference risk—these organizations understand that governance is existential. They’re my people.
I work with executive leadership at mid-to-enterprise scale organizations in heavily regulated industries. My typical engagement is with General Counsels, CIOs, Chief AI Officers, and compliance leaders who are tasked with building AI governance from the ground up—or rebooting it after a misstep. They’re pragmatic. They know governance is mandatory. They’re looking for someone who speaks both business and technology and can actually design systems that work.
If you’re at a point where AI is moving faster than your governance infrastructure can handle, where regulators are knocking, or where you’re building a center of excellence for AI—let’s talk. I help you move quickly without leaving risk on the table.