Project GOAT – AI-Enabled Learning Platform (Enterprise UX)

Designing an AI-driven onboarding and enablement experience for customer service teams at CVS

  • Role

    UX Lead/Product Designer

  • Tools

    Figma, Miro, Jira, Microsoft word, & Microsoft powerpoint

Overview

Designed an AI-powered learning platform to support onboarding and continuous development for customer service representatives. The platform combines guided learning, real-time AI assistance, and escalation workflows to improve knowledge retention and reduce dependency on trainers. I led the UX workstream, defining user flows, dashboards, and interaction patterns for a scalable enterprise system.

Target Users

The platform was designed to support three primary user groups, each with distinct needs and responsibilities

Learners

Primary users on the platform, responsible for onboarding and continuous development

Needs:

  • Clear structured learning pat

  • Real-time assistance while performing tasks

  • Visibility into progress and performance

  • Quick access to help when blocked

Design Focus:

  • Simplified dashboard

  • AI-Assisted guidance

  • Personalized Learning Journeys

Trainers (Subject matter experts)

Responsible for guiding learners, resolving

escalations, and ensuring knowledge accuracy

Needs:

  • Visibility into learner progress and challenges

  • Efficient handling of escalations

  • Ability to provide timely, contextual support

  • Insights into knowledge gaps

Design Focus:

  • Escalation management workflows

  • Communication touchpoints

  • Performance visibility

Admins (program/operations managers)

Oversee the learning ecosystem, ensuring alignment with business goals and performance metrics

Needs:

  • Monitoring system performance and engagement

  • Managing learning content and structure

  • Tracking completion rates and effectiveness

  • Ensuring scalability across teams

Design Focus:

  • System-level dashboards

  • Analytics and reporting

  • Content workflow management

Problem

Business Problems

  • Fragmented onboarding experience across tools

  • High dependency on trainers for support

  • Slow ramp-up time for new hires

User Problems (Learners)

  • Unclear learning path and next steps

  • Difficulty finding answers quickly

  • No personalized guidance

User Problems (Trainers/Admins)

  • Limited visibility into learner progress

  • Manual escalation handling

  • Lack of scalable system support

Solution

Guided Learning Dashboard

Designed a centralized dashboard providing personalized learning paths, progress tracking, and quick access to modules.

AI Assistant (Core Feature)

Introduced an AI-driven assistant to provide real-time support, answer questions, and guide users through learning workflows.

End to End User flows

IA Diagram

Key Design Decisions

  • Persistent AI Assistant
    → Enables quick support without disrupting workflow

  • Modular Learning Structure
    → Reduces cognitive overload

  • Simplified Escalation Flow
    → Minimizes friction and improves resolution speed

Impact

👤 User Impact

  • Faster access to answers via AI assistant

  • Clearer learning progression

  • Reduced confusion and friction

🧠 Team / Product Impact

  • Established UX foundation for a new AI-driven platform

  • Improved stakeholder alignment through UX artifacts and flows

  • Contributed to iterative improvements through feedback cycles

📈 Business Impact

  • Improved onboarding efficiency and clarity

  • Reduced dependency on trainers through self-service learning

  • Enabled scalable learning across teams

What I learned

  • Designing AI experiences requires balancing automation with human trust

  • Enterprise systems require clarity over visual complexity

  • Stakeholder alignment is critical when introducing new paradigms like AI learning

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Lennar | Real world Process (NDA) Note: This project is protected under NDA.