Vanguard - Individualization in AI Powered Experiences

Opportunity: As agentic experiences mature they have the opportunity to reduce cost by supplanting traditional live interactions. Clients will engage with these tools when they are aligned to client need and can help them solve problems faster than other existing means. We can drive client adoption of autonomous agents by having them learn and remember clients common needs and preferences, so these tools can address their needs quickly and efficiently.

Problem: AI powered experiences are typically built as a one size fits all solution. This can result in client frustration when needing to walk the agent through steps in a predefined workflow, re-explain a common request each time they begin a new session, or repeatedly correct an agent's default behavior/assumptions. Slow or frustrating experiences, agent misunderstanding, and client acumen of AI powered tools threaten adoption of autonomous systems that greatly reduce operational costs.

Vision: As clients interact with Vanguard through AI powered and traditional digital and voice channels, we can build a client profile of preferences, common goals/actions, and other gleaned data that can provide individualization for new interactions (both AI and traditional). From these exchanges we can create a baseline understanding of how the client views their portfolio, their individual goals, and agentic skills to address recurring needs. This additional context would result in a 'personal assistant' style experience; pre-fetching a portfolio analysis the client often asks for, remembering how the client described an account (e.g. emergency fund, down payment savings, etc.), or consistently presenting certain information aligned with their preference (e.g. always show my portfolio performance in comparison to the S&P).

Metrics: Reduced live agent escalation for clients, increased return usage rate to AI experiences, reduced frustration scoring on AI experiences.