The goal is to create an AI model for a solution, which in the context of the PL-500 exam, implies a Power Platform solution. The most appropriate and integrated tool for creating a custom image detection model within the Power Platform is AI Builder. AI Builder provides a low-code object detection model specifically for scenarios like identifying objects (such as broken bones) in images. While Azure Machine Learning is a powerful platform for creating custom models, AI Builder is the intended, native service for this task within the Power Platform ecosystem, requiring no specialized data science expertise.

A. This is incorrect because AI Builder is the primary, integrated Power Platform service for creating custom AI models for tasks like object detection, making it the more appropriate choice for a PL-500 solution.

1. Microsoft Learn, AI Builder Documentation. "Overview of the object detection model - AI Builder". This document explicitly states that AI Builder's object detection model can be trained to recognize specific objects in images, which directly aligns with the requirement to detect broken bones in X-rays. It is presented as the Power Platform's native solution for this task.

2. Microsoft Learn, Power Automate Documentation. "Use the object detection prebuilt model in Power Automate". This guide shows how to integrate the AI Builder object detection model directly into Power Platform solutions, reinforcing its role as the intended tool.

3. Microsoft Learn, Power Platform Documentation. "Compare AI Builder and Azure Machine Learning". This resource clarifies the use cases. It states, "AI Builder is the right solution for you if... You want to use AI to detect objects in images... in a low-code environment." It positions Azure Machine Learning for scenarios requiring data scientists and complex, code-first model development, which is not specified in the question.