THE JOURNAL
Field notes on privacy operations, AI governance, and the regulatory landscape — written by the people who run the programs.
Who's Watching Your AI After You Hit Approve?
Approval is not the end of AI oversight — it is the start of it. What continuous monitoring actually requires, who should own it, and what regulators expect to see when they come asking.
READ ARTICLE →Building an Agentic Enterprise
IBM reports $3.5 billion in productivity gains from AI agents. McKinsey says workflow redesign, not tooling, separates the winners. Neither number tells you what the same architecture does to your privacy risk. This does.
Secure AI Adoption for Regulated Businesses: How Advisori Helps Clients Build with Confidence
How we help regulated clients adopt AI without tripping over GDPR, HIPAA, or their own procurement process. A walkthrough of the review we run before anything ships.
AI Agents Need Guardrails Before They Get Autonomy
AI agents create new privacy, security, and compliance risks. Learn how to control prompt injection, data leakage, hallucinations, and excessive agency before they become business problems.
Data Protection in Clinical Trials: What Sponsors Need to Get Right
Clinical trials process some of the most sensitive personal data imaginable. For CPOs, DPOs, and privacy counsel, three documents carry the most legal and operational risk — Clinical Trial Agreements, vendor Data Processing Agreements, and Informed Consent Forms. This guide shows you how to get all three right.
MCP and the Future of Privacy Governance
A new protocol is quietly becoming the connective tissue between AI agents and the applications they act on. For privacy professionals, MCP is both the best opportunity and the sharpest risk the agentic era has produced.
The Autonomy Problem: Why AI Agents Demand Privacy-by-Design
Autonomous AI agents are moving from experiment to enterprise infrastructure. The privacy risks are no longer theoretical — and the controls must be designed in before the first line of code is written.
Vibe Coding, Agentic AI, And The New Risk-Assessment Burden For CPOs
Software is increasingly written by agents and reviewed by nobody. What that does to the risk assessments CPOs are legally required to stand behind.
Traditional Machine Learning: Data In, Decisions Out
Before the hype — how classic ML systems collect and use personal data, and where the legal obligations attach at each stage of the model lifecycle.
A Comprehensive Guide to CCPA Risk Assessment Requirements
California's Article 10 risk-assessment rules, explained — who is covered, what has to be documented, and when the first filings are due.
Drowning in PIAs? How AI Automation Rescues Overwhelmed Privacy Teams
Privacy teams are averaging more assessments than they can read. Where automation genuinely helps — and where it just relocates the backlog.