To equip RIA professionals with the skills and governance frameworks to use generative and predictive AI tools for enhancing client communication, segmentation, onboarding, and personalization without violating client privacy, fiduciary duty, or marketing rules.

Module Overviews

Module 1: Foundations of AI in Client Engagement

• What AI can/cannot do in a fiduciary firm

• The spectrum: automation vs. generative AI vs. predictive AI

• Use cases: Content generation, behavior modeling, chatbot augmentation

• Real-world RIA case studies

• Risk framing: Data exposure, over-personalization, hallucinations

Takeaway: “AI can support personalization—but people ensure it’s personal.”

Module 2: Client Communication with AI

• Drafting empathy-aligned emails, event invites, and client updates

• Tone modeling for different personas (e.g., delegators vs. validators)

• Real-time language tuning using tools like GrammarlyGO or Writer

• Avoiding SEC Rule 206(4)-1 pitfalls (e.g., promissory or misleading language)

• Redline lab: Edit AI-drafted client email together as a group

Output: Learners create an AI-assisted but human-edited client outreach template.

Module 3: Predictive Personalization (Without Crossing the Line)

• Segmenting clients using AI without using personal identifiers

• LLMs vs. machine learning for anticipating client needs

• Case examples: “Topical nudges” based on behavior (e.g., sending estate planning tips after a family change)

• Consent management for personalization engines

• Discussion: When does personalization feel invasive?

Deliverable: Build a “segment-safe” personalization campaign framework.

Module 4: AI in Client Journey Mapping

• Mapping onboarding flows with AI-assisted prompts

• Automating event-based touchpoints (e.g., AI generates follow-ups after 401(k) rollover)

• AI for flagging service gaps or predicting churn risk

• Practical walkthrough: Use Copilot to visualize a multi-step journey for new retirees

Capstone Exercise: Design a client journey with AI-assisted automation—but include human check-ins.

Module 5: Privacy, Consent & Compliance

• Reg S-P and how it applies to personalization

• Consent frameworks: What clients must opt into

• Using AI tools that support zero-data retention

• SEC marketing rule overlaps (no implied advice, testimonials, performance)

• Vendor checklist: What to ask your tech providers

Checklist: Create a “Compliant AI Personalization Use Policy” for client engagement.

Module 6: Hands-On Labs & Use Cases

• Red team/blue team activity: Spot compliance flags in AI-generated outreach

• Compare 3 tools (e.g., ChatGPT, Jasper, Microsoft Copilot) for suitability

• Scenario simulation: AI drafts message to client near retirement, team evaluates tone, risk, and value

• Ethical dilemma discussion: When AI knows “too much”

Gamified Wrap-Up: AI Personalization Simulation—each learner builds and tests a mini-campaign within firm-guardrails.

Learning Materials & Resources

• Video explainers (e.g., “Personalization vs. Manipulation”)

• Prompt playbooks for client personas

• AI ethics & compliance glossaries

• SEC AI policy excerpts

• Case study vault (real-world RIA examples anonymized)

Assessments & Certification

• Knowledge checks at end of each module (scenario-based)

• Final capstone simulation: “Design a 3-touch client experience campaign using AI responsibly”

Credential: Certified in Ethical AI Personalization for Client Engagement