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    The AI Records Retention Playbook

    A decision framework for SEC Rule 204-2, FINRA Rule 17a-4, and the 2026 examination environment.

    Executive Guide

    AI adoption is accelerating across investment advisers and wealth management firms. Most organizations are still uncertain which AI interactions must be retained, what can be defensibly deleted, and how regulators will evaluate AI-generated business records.

    This executive guide provides a practical framework for building a compliant, defensible AI records retention program.

    30
    AI use cases classified
    90
    Day implementation roadmap
    12
    Point enforcement risk assessment
    5
    Question decision framework

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    The Value Creation Math

    Why This Matters for You

    As AI adoption accelerates across investment advisers and wealth management firms, many organizations are making records retention decisions without a defensible framework. Some firms retain too little and risk being unable to reconstruct how recommendations and business decisions were generated. Others retain everything, creating unnecessary discovery exposure and operational burden. This executive guide provides a practical decision framework to help compliance, legal, operations, and technology leaders establish governance for AI-generated content and prepare for increasing regulatory scrutiny.

    What You'll Learn

    Inside the Playbook

    A practical framework for AI records retention, governance, compliance, and examination readiness.

    01 - Decision Framework
    The Capacity Decision Tree for determining what AI-generated records should be retained and what can be defensibly deleted.
    02 - Classification Matrix
    A 30-use-case classification framework that maps AI interactions to retention and compliance requirements.
    03 - Retention Architecture
    Evaluate retention models, governance structures, and controls using the Retention Architecture Scorecard.
    04 - Readiness Roadmap
    Implement the 90-day roadmap, complete the 12-point risk assessment, and prepare for future examinations.

    Executive Guide

    Ready to Build a Defensible AI Records Retention Framework?

    Learn how to classify AI interactions, apply retention requirements consistently, reduce discovery liability, and prepare your organization for increased SEC and FINRA scrutiny. The guide includes the Capacity Decision Tree, 30-Use-Case Classification Matrix, Retention Architecture Scorecard, 90-Day Roadmap, and 12-Point Enforcement Risk Assessment.

    Download the Executive Guide →