Operational AI, or operational artificial intelligence, is a type of software technology used by computers and other devices that mimics the cognitive functions of the human brain. It is also used to identify patterns in data, make decisions, and classify objects and events.
At its core, operational AI is an autonomous technology that uses machine learning and natural language processing to process information and act on it. This allows it to react differently to different stimuli, learn from mistakes, and adjust its behavior accordingly. It is the foundation of many of today’s advancement in intelligent technology, such as facial recognition and self-driving cars.
Apart from simply reacting to stimuli, operational AI can be used to identify errors and optimize production operations. This reduces costs and increases efficiency. For example, it can use analytics and machine learning to anticipate customer demands and restock shelves accordingly, or even improve how robots are used in manufacturing logistics.
In addition, operational AI can be used to detect anomalies in financial transactions, as well as predict customer needs and preferences. This enables businesses to develop more personalized customer experiences.
Most importantly, operational AI must be monitored to ensure proper functioning. No AI system is perfect, and as such, potential risks must be monitored and addressed. AI security is a growing concern, and as such, there must be continuous vigilance over operational AI.
Finally, operational AI exists as part of a larger trend known as ‘automation’, in which automated processes are used to speed up and increase the efficiency of digital operations. As technology continues to improve, the scope of automatable operations will expand as well, giving way to a future in which robots and AI systems take on most of the jobs humans have traditionally done.
