Operational AI

Operational AI is an area of artificial intelligence (AI) that involves applications and systems used to produce high-level decisions and actions in operational contexts. It is distinct from learning AI, which is concerned with learning from data and generalizing concepts, and from weak AI, which is concerned with task-specific performance. In contrast, Operational AI focuses on providing interactive decision-making abilities to a user in operational and data-driven contexts, such as enterprise automation, operational optimization, and production planning.

At its core, Operational AI utilizes data, models, and analytics to generate output information that enables a user to interact with complex datasets, optimize outcomes, manage inventory and resources, facilitate production, and automate operations. This output information can be used to inform decisions in dynamic, real-time operational contexts and to maximize output through intelligent optimization.

Organizations and to a greater extent, Operational AI, require reliable data sources to create and maintain the accuracy of their efforts in order to reduce risks and decision-making errors. This becomes all-the-more crucial in safety-critical environments, such as air traffic control, that can be driven by Operational AI.

In addition to its primary role in making decisions and providing input to users, Operational AI is also increasingly being used in autonomous context, such as robots. Autonomous robots running Operational AI programs are becoming commonplace in industries such as manufacturing, agriculture, healthcare, and transportation. They are often designed to interact with humans, leveraging human-machine interfaces to complete complex tasks.

The overall goal of Operational AI is to create user-friendly, efficient, and automated applications and systems that enable individuals and organizations to make better decisions faster and more accurately than traditional methods. In that regard, it is a powerful tool for enterprises interested in furthering their development and pursuing cost and time savings.