Who we are / senior leadership + accountable delivery
davisAIgov is an advisory and assurance practice led by Richard E. Davis. We help organizations understand technology risk, verify what controls actually do, and explain difficult technical facts when business decisions, regulatory scrutiny or disputes depend on them.
Our experience connects enterprise leadership, cross-border review, major-incident preservation and large-scale data analysis to the practical challenges of AI governance.
Leadership
The work is led by a principal who has managed security operations and worked where technical evidence must withstand detailed questioning.
Founder and Principal · CISO · AI and Cyber-GRC Advisor
Richard previously served as a Merck Director of Compliance and Risk Management. His supplied CV describes responsibility for five cybersecurity functions: Incident Response, Threat Defense Operations, Cyber Threat Intelligence, Data Loss Prevention and Digital Forensics.
His cross-functional work brought Legal, Privacy, Global Security, engineering, R&D and business leaders into the same risk conversation. His CV also describes establishing an Enterprise Security Analytics Working Group and developing Deep Content Awareness to connect information classification with protection.
That combination informs our approach to AI: establish the business purpose, understand the systems and data involved, set operating limits, test what happens and preserve the evidence.
Additional experience / current relevance
CISO work at a NYDFS-regulated institution connects incident recovery, forensic preservation, control remediation and examination evidence. The goal is a response that restores operations and leaves a record leaders can explain.
Richard's TIAA consulting work included application-portfolio risk, technology debt, AI safeguards and analysis of AML/KYC technology failures. That experience helps turn fragmented ownership into a prioritized operating plan.
At IQVIA, his security-architecture work addressed acquired bioinformatics, AI and machine-learning companies. The connection to today's diligence is practical: identify inherited exposure and make remediation part of the integration plan.
Examples drawn from the supplied CV. Prior career organizations are not presented as current clients or endorsers of davisAIgov.
Experience with consequences
These are examples of Richard's prior career work, not claims that today's AI systems existed in those engagements.
Merck / enterprise leadership
AI governance has the same coordination problem: a model owner, data owner, system operator and business sponsor may each see only part of the risk. We help assign decision rights, test data and tool permissions, align monitoring, and define who acts when a boundary is crossed.
See the experience and its applicationJapan / cross-border regulatory review
An AI-assisted review still needs clear instructions, trained reviewers, traceable decisions and human responsibility. We bring that operating discipline to regulatory response, AI review workflows and transaction diligence, with sampling and exception handling defined for the engagement.
See the experience and its applicationBP / Deepwater Horizon response
After ransomware or an AI-related incident, organizations must distinguish what was instructed from what actually happened. We map relevant systems and custodians, preserve logs and decision records, reconstruct events and identify gaps for counsel and incident leaders to resolve.
See the experience and its applicationMazzei / complex data and technical testimony
When AI decisions are challenged, an attractive dashboard is not enough. We examine source systems, data definitions, joins, transformations, model or rule versions and exceptions to determine which conclusions can be reproduced, which require more evidence and which remain unsupported.
See the experience and its applicationThe davisAIgov Expert Network
We define the decision, scope, evidence needed and acceptance criteria with the client. A named engagement lead stays accountable.
Independent specialists and technology partners are selected for the assignment. Roles, qualifications, conflicts and delivery terms are disclosed.
We review material findings, retain the supporting records and explain what the evidence can and cannot establish.
Career and engagement descriptions draw on Richard's supplied CV and firsthand account. Named organizations are historical context, not endorsements or current-client claims. The network is a delivery model, not a claim of a permanently employed bench. Legal interpretation and representation remain with licensed counsel.
Continue the conversation
See the business decisions, operating pressures and stakeholder responsibilities our work supports.
Career evidence: public records, published professional biographies and principal-provided engagement details are distinguished in our leadership experience notes. Named organizations do not imply endorsement.
