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Building Conversational AI Agents

A Standardized Framework to Design, Evaluate, and Automate Human-Led Workflows

Overview

This repository contains my Master's Thesis. The dissertation proposes a standardized Product Owner-led framework for designing, implementing, evaluating, and scaling conversational AI agents capable of supporting human-led operational workflows. The framework is validated through a real-world healthcare case study involving member activation within a digital physical therapy platform.

Research Objectives

  • Identify suitable workflows for conversational AI
  • Design a reusable implementation framework
  • Develop evaluation criteria
  • Define pilot and scaling strategies
  • Assess operational and business impact

Research Questions

RQ1: How can conversational AI agents be systematically designed to support human-led workflows? RQ2: How should conversational AI agents be evaluated before operational deployment?

Main Contributions

  • Standardized AI agent development framework
  • Product Owner decision process
  • Evaluation methodology
  • Pilot and scaling strategy
  • Healthcare case study

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Master's Thesis proposing a standardized Product Owner-led framework for designing, evaluating, piloting, and scaling conversational AI agents that automate human-led workflows.

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