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

Designing human-machine collaboration with cognitive automation

In the previous section, we explored the spectrum of office work and its relative automation potentials. Companies look for a more efficient and effective way to perform office work by leveraging automation. Office work does not comprise a single activity but a sequence of activities that make up a process. Full automation of the end-to-end (E2E) process may be the eventual goal. However, a more realistic goal is good human-machine collaboration to drive efficiency and effectiveness with currently available technology. Therefore, it is important to understand how humans and machines work differently and the best way to think through a human-machine collaboration when designing cognitive automation.

Demonstrating human-machine collaboration with examples

When we look at office work at a process level instead of at an activity level, we find that this is a collection of activities with different automation potentials...