Book Image

Democratizing Artificial Intelligence with UiPath

By : Fanny Ip, Jeremiah Crowley
Book Image

Democratizing Artificial Intelligence with UiPath

By: Fanny Ip, Jeremiah Crowley

Overview of this book

Artificial intelligence (AI) enables enterprises to optimize business processes that are probabilistic, highly variable, and require cognitive abilities with unstructured data. Many believe there is a steep learning curve with AI, however, the goal of our book is to lower the barrier to using AI. This practical guide to AI with UiPath will help RPA developers and tech-savvy business users learn how to incorporate cognitive abilities into business process optimization. With the hands-on approach of this book, you'll quickly be on your way to implementing cognitive automation to solve everyday business problems. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book will help you understand the power of AI and give you an overview of the relevant out-of-the-box models. You’ll learn about cognitive AI in the context of RPA, the basics of machine learning, and how to apply cognitive automation within the development lifecycle. You’ll then put your skills to test by building three use cases with UiPath Document Understanding, UiPath AI Center, and Druid. By the end of this AI book, you'll be able to build UiPath automations with the cognitive capabilities of intelligent document processing, machine learning, and chatbots, while understanding the development lifecycle.
Table of Contents (16 chapters)
1
Section 1: The Basics
5
Section 2: The Development Life Cycle with AI Center and Document Understanding
10
Section 3: Building with UiPath Document Understanding, AI Center, and Druid

Chapter 5: Designing Automation with End User Considerations

Once automation opportunities have been identified, the next milestone in the automation journey is focused on requirements gathering. During this phase, it is imperative to gather as much context as possible around the end user's requirements and goals for automation to ensure that cognitive automation can achieve the end user's target goals. Understanding the target goals of the use case will determine the future success of applying cognitive automation to an opportunity.

Every automation should be designed with the end user's considerations in mind. Automation that is difficult for the end user to interact with is automation that runs the risk of being unused; thus, in this chapter, we will first focus on gathering the end user's requirements, then move toward setting the target goals of future state automation. Finally, we will dive into how to design a future state automation solution.

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