Book Image

Power Platform and the AI Revolution

By : Aaron Guilmette
Book Image

Power Platform and the AI Revolution

By: Aaron Guilmette

Overview of this book

In this AI era, employing leading machine learning and AI models such as ChatGPT for responding to customer feedback and prototyping applications is crucial to drive business success in the competitive market. This book is an indispensable guide to integrating cutting-edge technology into business operations and leveraging AI to analyze sentiment at scale, helping free up valuable time to enhance customer relationships. Immerse yourself in the future of AI-enabled application development by working with Power Automate, Power Apps, and the new Copilot Studio. With this book, you’ll learn foundational AI concepts as you explore the extensive capabilities of the low-code Power Platform. You’ll see how Microsoft's advanced machine learning technologies can streamline common business tasks such as extracting key data elements from customer documents, reviewing customer emails, and validating passports and drivers’ licenses. The book also guides you in harnessing the power of generative AI to expedite tasks like creating executive summaries, building presentations, and analyzing resumes. You’ll build apps using natural language prompting and see how ChatGPT can be used to power chatbots in your organization. By the end of this book, you’ll have charted your path to developing your own reusable AI automation patterns to propel your business operations into the future.
Table of Contents (16 chapters)

What is sentiment analysis, anyway?

Sentiment analysis, simply put, answers the question, “What type of feelings are present in this content?” Power Platform’s sentiment analysis model can examine a piece of content and return one of the following four sentiments:

  • Positive
  • Negative
  • Neutral
  • Mixed

When processing text, the sentiment analysis AI model returns a sentiment value for each sentence, as well as the content as a whole. In addition to the sentiment value, sentiment analysis provides confidence scoring, indicating how confident the model is in its assessment, on a scale of 0 to 1, where 1 represents more confidence and 0 represents less confidence. Sentiment analysis does have its limitations, however – for example, if the content has incorrect or improper word usage – that may influence the ratings.

The scenario in this chapter is based on a fictional company that uses a customer service mailbox as a funnel for...