Gartner defines Artificial intelligence as technology that [appears to] emulate human performance typically by learning, coming to its own conclusions, appearing to understand complex content, engaging in natural dialog with people, enhancing human cognitive performance (also known as cognitive computing) or replacing people on execution of non-routine tasks.

Mackenzie & Company have noted AI technologies focusing on the “narrow” definition of AI, which performs one narrow task, as opposed to artificial general intelligence, or AGI, which seeks to be able to perform any intellectual task that a human can do. M&C focus on the narrow AI because it has near-term business potential, while AGI has yet to arrive.

Boston Consulting Group mention that Artificial Intelligence is a similar construct to AI and AGI, however they note about the important meanings of action and ongoing learning:

‘A trained algorithm can accept live data and deliver actions—a credit score decision and its automated delivery to a customer, for example, or a cancer diagnosis based on a medical image, or a left-hand turn into oncoming traffic by a driver-less car. Although this data-to-action process does not differ from the workings of standard computer programs, an AI system continues to learn and transform itself. The data is thus a source of both action and self-improvement—as it is for a business executive, who makes decisions based on facts and uses those facts to refine future decisions’

See what Deloitte insights say about AI Technology Trends 2018:

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