Hype vs. Reality in AI & ML: Where are the Concrete Business Benefits?
The conversation on artificial intelligence and machine learning is still largely driven by hype. But concrete business benefits exist for narrow AI solutions, and it is time to separate hype from reality. This leadership brief identifies the characteristics of successful AI use cases, provides examples across multiple industries and business departments, and provides recommendations on distinguishing AI solutions that can deliver value.
1 Executive Summary
The conversation surrounding artificial Intelligence and machine learning is still largely driven by hype. But this degrades the potential of narrow AI solutions; concrete benefits for the enterprise exist and can be leveraged without causing a moral dilemma. A more constructive method is to discuss realistic AI solutions rather than futuristic scenarios that are more an exercise in ethics than in business sense.
It is necessary to define the difference between general AI and narrow AI in order to separate hype from reality. General AI is the ability of a machine to intuitively react to situations that it has not been trained to handle in an intelligent, human way, and does not yet exist. Narrow AI, sometimes called applied AI, is what exists today and enables programs to independently complete a task that it has been trained to do.
A narrow AI use case with solid business benefits requires access to historical data, a constant flow of real-time data, a repetitive task to be completed, and sufficient control by the implementing company. Such solutions can be applied across all industries as well as different departments.
Five examples of applications with clear business benefits are described. Equipped with the insights from this leadership brief, you should be able to separate the hype from reality, where narrow AI can bring value to your unique business.
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