Artificial Intelligence in Management
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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.
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Chapter 3: Autonomous systems in value generation

Andrzej Wodecki

Abstract

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.

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