Artificial intelligence in the real world | Shreya

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Shreya
Jun 2, 2022

Artificial intelligence in the real world

We’ll look at the various categories of AI being employed and provide a framework for how companies should begin to build up their cognitive capabilities in the next several years to achieve their business objectives.

It is useful for companies to look at AI through the lens of business capabilities rather than technologies. Broadly speaking, AI can support three important business needs: 1. Automating business processes 2. Gaining insight through data analysis 3. Engaging with customers and employees

The most common type is the automation of digital and physical tasks—typically back-office administrative and financial activities—using robotic process automation technologies. RPA is more advanced than earlier business-process automation tools, because the “robots” act like a human inputting and consuming information from multiple IT systems.

RPA is least expensive and least smart too. The second most common type of projects used algorithms to detect patterns in vast volumes of data and interpret their meaning. Think of it as “analytics on steroids.”

Cognitive insight applications are typically used to improve performance on jobs only machines can do—tasks such as programmatic ad buying that involve such high-speed data crunching and automation that they’ve long been beyond human ability.

Projects that engage employees and customers using natural language processing chatbots, intelligent agents, and machine learning were the least common type.


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