Artificial Intelligence in Management
Show Less

Artificial Intelligence in Management

Self-learning and Autonomous Systems as Key Drivers of Value Creation

Andrzej Wodecki

Autonomous systems are on the frontiers of Artificial Intelligence (AI) research, and they are slowly finding their business applications. Driven mostly by Reinforcement Learning (RL) methods (one of the most difficult, but also the most promising modern AI algorithms), autonomous systems help create self-learning and self-optimising systems, ranging from simple game-playing agents to robots able to efficiently act in completely new environments. Based on in-depth study of more than 100 projects, Andrzej Wodecki explores RL as a key component of modern digital technologies, its real-life applications to activities in a value chain and the ways in which it impacts different industries.
Show Summary Details
You do not have access to this content

Chapter 3: Autonomous systems in value generation

Andrzej Wodecki


Chapter 3, based on the case studies presented earlier, presents best practices of autonomous systems implementations, classifies the values they can provide, and proposes a universal model for designing business cases for artificial intelligence in modern organizations. In the first section, we show the practical aspects of Ai deployments, from initiation, implementation to fixation of change. In the next step, we summarize the values generated by Ai by dividing them into revenue-generating, cost-reducing, and risk-minimizing. Finally, we present the AIR Management model based on the analogy to human resources management systems, which can be a useful metaphor for designing and implementing Ai in organizations.

You are not authenticated to view the full text of this chapter or article.

Elgaronline requires a subscription or purchase to access the full text of books or journals. Please login through your library system or with your personal username and password on the homepage.

Non-subscribers can freely search the site, view abstracts/ extracts and download selected front matter and introductory chapters for personal use.

Your library may not have purchased all subject areas. If you are authenticated and think you should have access to this title, please contact your librarian.

Further information

or login to access all content.