AI Virtual Assistant for Order Management

Designing AI-Driven Workflows for Healthcare Staffing Efficiency

Role

UX Lead

Industry

Healthcare

Duration

2 months

Overview

Led the design of a virtual assistant tool to streamline the order creation and staffing process for ShiftWise™, an AMN product and a healthcare workforce management platform. This initiative aimed to reduce manual entry, improve accuracy, and boost productivity—while showcasing the potential of AI in enterprise healthcare systems.

“The AI demo was way ahead of the game... the team’s familiarity with the product made it easy to deliver more than what was expected.”
— Director, Product Management

The Challenge

Healthcare staffing platforms face high volumes of manual data entry, order errors, and inefficient workflows. Our goal was to:

  • Automate order creation via chat and email parsing

  • Improve search and summarization of order data

  • Support bulk actions and reduce friction in daily tasks

Key Users & Personas

  • Account Managers – Create and manage staffing orders

  • MSP Managers – Oversee reporting and compliance

  • Clinicians & Admins – Interact with scheduling and credentialing tools

Overview

Led the design of a virtual assistant tool to streamline the order creation and staffing process for ShiftWise™, an AMN product and a healthcare workforce management platform. This initiative aimed to reduce manual entry, improve accuracy, and boost productivity—while showcasing the potential of AI in enterprise healthcare systems.

“The AI demo was way ahead of the game... the team’s familiarity with the product made it easy to deliver more than what was expected.”
— Director, Product Management

The Challenge

Healthcare staffing platforms face high volumes of manual data entry, order errors, and inefficient workflows. Our goal was to:

  • Automate order creation via chat and email parsing

  • Improve search and summarization of order data

  • Support bulk actions and reduce friction in daily tasks

Key Users & Personas

  • Account Managers – Create and manage staffing orders

  • MSP Managers – Oversee reporting and compliance

  • Clinicians & Admins – Interact with scheduling and credentialing tools

Research & Discovery

  • Mapped current vs. future-state order flows

  • Identified pain points in manual entry and email-based intake

  • Audited existing UI patterns and tested early concepts with a POC

  • Collaborated with stakeholders to validate and refine the assistant’s role

The Solution

We designed a virtual assistant that:

  • Parses emails and chat prompts to auto-generate orders

  • Flags missing information and suggests next steps

  • Offers a wizard-like interface for bulk actions and order queries

  • Integrates seamlessly into existing workflows with minimal disruption

Implementation Strategy

  • Defined a phased rollout plan with clear objectives and resource needs

  • Outlined data handling, AI training, and MVP scope

  • Created a roadmap for iterative testing and stakeholder feedback

Impact

  • Reduced manual entry and order errors

  • Improved user productivity and task completion speed

  • Received strong stakeholder buy-in and positive feedback

  • Set the foundation for future AI-driven features across the platform

Reflection

This project demonstrated how AI can enhance enterprise UX when paired with thoughtful design. By automating repetitive tasks and supporting user workflows, we helped healthcare teams focus more on patient care—and less on administrative overhead.

Impact

  • Reduced manual entry and order errors

  • Improved user productivity and task completion speed

  • Received strong stakeholder buy-in and positive feedback

  • Set the foundation for future AI-driven features across the platform

Reflection

This project demonstrated how AI can enhance enterprise UX when paired with thoughtful design. By automating repetitive tasks and supporting user workflows, we helped healthcare teams focus more on patient care—and less on administrative overhead.

Other projects

Copyright 2025 by Rana Rizcalla

Copyright 2025 by Rana Rizcalla

Copyright 2025 by Rana Rizcalla