Navigating Regulatory Compliance in AI Recommendations

⚠️Privacy Risks in AI Management: Lessons from Italy’s DeepSeek Ban⚠️ Italy’s recent ban on #DeepSeek over privacy concerns underscores the need for organizations to integrate stronger data protection measures into their AI Management System (#AIMS), AI Impact Assessment (#AIIA), and AI Risk Assessment (#AIRA). Ensuring compliance with #ISO42001, #ISO42005 (DIS), #ISO23894, and #ISO27701 (DIS) guidelines is now more material than ever. 1. Strengthening AI Management Systems (AIMS) with Privacy Controls 🔑Key Considerations: 🔸ISO 42001 Clause 6.1.2 (AI Risk Assessment): Organizations must integrate privacy risk evaluations into their AI management framework. 🔸ISO 42001 Clause 6.1.4 (AI System Impact Assessment): Requires assessing AI system risks, including personal data exposure and third-party data handling. 🔸ISO 27701 Clause 5.2 (Privacy Policy): Calls for explicit privacy commitments in AI policies to ensure alignment with global data protection laws. 🪛Implementation Example: Establish an AI Data Protection Policy that incorporates ISO27701 guidelines and explicitly defines how AI models handle user data. 2. Enhancing AI Impact Assessments (AIIA) to Address Privacy Risks 🔑Key Considerations: 🔸ISO 42005 Clause 4.7 (Sensitive Use & Impact Thresholds): Mandates defining thresholds for AI systems handling personal data. 🔸ISO 42005 Clause 5.8 (Potential AI System Harms & Benefits): Identifies risks of data misuse, profiling, and unauthorized access. 🔸ISO 27701 Clause A.1.2.6 (Privacy Impact Assessment): Requires documenting how AI systems process personally identifiable information (#PII). 🪛 Implementation Example: Conduct a Privacy Impact Assessment (#PIA) during AI system design to evaluate data collection, retention policies, and user consent mechanisms. 3. Integrating AI Risk Assessments (AIRA) to Mitigate Regulatory Exposure 🔑Key Considerations: 🔸ISO 23894 Clause 6.4.2 (Risk Identification): Calls for AI models to identify and mitigate privacy risks tied to automated decision-making. 🔸ISO 23894 Clause 6.4.4 (Risk Evaluation): Evaluates the consequences of noncompliance with regulations like #GDPR. 🔸ISO 27701 Clause A.1.3.7 (Access, Correction, & Erasure): Ensures AI systems respect user rights to modify or delete their data. 🪛 Implementation Example: Establish compliance audits that review AI data handling practices against evolving regulatory standards. ➡️ Final Thoughts: Governance Can’t Wait The DeepSeek ban is a clear warning that privacy safeguards in AIMS, AIIA, and AIRA aren’t optional. They’re essential for regulatory compliance, stakeholder trust, and business resilience. 🔑 Key actions: ◻️Adopt AI privacy and governance frameworks (ISO42001 & 27701). ◻️Conduct AI impact assessments to preempt regulatory concerns (ISO 42005). ◻️Align risk assessments with global privacy laws (ISO23894 & 27701).   Privacy-first AI shouldn't be seen just as a cost of doing business, it’s actually your new competitive advantage.

The Future of Privacy Forum and OneTrust have published an updated guide to help organizations navigate Conformity Assessments (CAs) under the final version of the EU #Artificial Intelligence Act. CAs are a cornerstone of the EU AI Act's compliance framework and will be critical for any organization developing or deploying high-risk #AIsystems in the EU. The guide offers a clear and practical framework for assessing whether, when, and how a CA must be conducted. It also clarifies the role of CAs as an overarching accountability mechanism within the #AIAct. This guide: - Provides a step-by-step roadmap for conducting a Conformity Assessment under the EU AI Act. - Presents CAs as essential tools for ensuring both product safety and regulatory compliance. - Identifies the key questions organizations must ask to determine if they are subject to CA obligations. - Explains the procedural differences between internal and third-party assessments, including timing and responsibility. - Details the specific compliance requirements for high-risk #AI systems. - Highlights the role of documentation and how related obligations intersect with the CA process. - Discusses the use of harmonized standards and how they can create a presumption of conformity under the Act. This guide serves as a practical resource for understanding the conformity assessment process and supporting organizations in preparing for compliance with the EU AI Act.

Over the past 2.5 years of building Zocks, I’ve talked to many Chief Compliance Officers at large financial firms about how to ensure compliance when using AI. Here are 4 areas I always recommend they cover: 1) Consent Since AI analyzes a lot of data and conversations, I tell them to make sure FAs get consent from their clients. They can get consent in multiple ways: - Pre-meeting email -Have the advisor specifically ask during the meeting (Zocks detects and reports on this automatically) - Include it in the paperwork The key is notifying and getting clear consent that the firm will use AI systems. 2) Output review by FAs AI systems in financial planning are designed to aid advisors – not automate everything. FAs are still responsible for reviewing AI outputs, ensuring that the system only captures necessary data, and checking it before entering it into books and records. That’s why I always emphasize the workflow we developed for Zocks: it ensures advisors review outputs before they’re finalized. 3) Supervising & archiving policy Frankly, FINRA and SEC regulations around AI are a bit vague and open to interpretation. We expect many changes ahead, especially around supervision, archiving, and privacy. What do you consider books and records and is that clear? Firms need a clear, documented policy on supervising and archiving. Their AI system must be flexible enough to adapt as the policy changes, or they’ll need to overhaul it. Spot checks or supervision through the system itself should be part of this policy to ensure compliance. 4) Recommendations Some AI systems offer recommendations. Zocks doesn’t. In fact, I tell Chief Compliance Officers to be cautious around recommendations. Why? They need to understand the data points driving the recommendation, ensure FAs agree with it, and not assume it's always correct. Zocks factually reports instead of recommending, which I think is safer from a compliance perspective. Final thoughts: If you: - Get consent - Ensure FAs review outputs - Establish a supervising and archiving, or books and records  policy - Watch out for recommendations It will help you a lot with compliance. And when disputes arise, you’ll have the data to defend yourself, your firm, and your advisors. Any thoughts?