ABSTRACT

Artificial intelligence (AI) in its various forms –– machine learning, chatbots, robots, agents, etc. –– is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets.

With increasing business process and workflow maturity, coupled with recent trends in cloud computing, datafication, IoT, cybersecurity, and advanced analytics, there is an understanding that the challenges of tomorrow cannot be solely addressed by today’s people, processes, and products.

There is still considerable mystery, hype, and fear about AI in today’s world. A considerable amount of current discourse focuses on a dystopian future that could adversely affect humanity. Such opinions, with understandable fear of the unknown, don’t consider the history of human innovation, the current state of business and technology, or the primarily augmentative nature of tomorrow’s AI.

This book demystifies AI for the enterprise. It takes readers from the basics (definitions, state-of-the-art, etc.) to a multi-industry journey, and concludes with expert advice on everything an organization must do to succeed. Along the way, we debunk myths, provide practical pointers, and include best practices with applicable vignettes.

AI brings to enterprise the capabilities that promise new ways by which professionals can address both mundane and interesting challenges more efficiently, effectively, and collaboratively (with humans). The opportunity for tomorrow’s enterprise is to augment existing teams and resources with the power of AI in order to gain competitive advantage, discover new business models, establish or optimize new revenues, and achieve better customer and user satisfaction.

chapter Chapter 1|28 pages

AI Strategy for the Executive

chapter Chapter 2|28 pages

Learning Algorithms, Machine/Deep Learning, and Applied AI

A Conceptual Framework

chapter Chapter 3|34 pages

AI for Supply Chain Management

chapter Chapter 4|30 pages

HR and Talent Management

chapter Chapter 5|28 pages

Customer Experience Management

chapter Chapter 6|44 pages

AI in Financial Services

chapter Chapter 7|30 pages

Artificial Intelligence in Retail

chapter Chapter 8|41 pages

Visualization

chapter Chapter 9|24 pages

Solution Architectures

chapter Chapter 10|36 pages

AI and Corporate Social Responsibility

chapter Chapter 11|22 pages

Future of Enterprise AI