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Artificial Intelligence and DaaS

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We’ve discussed the need
to redefine enterprise intelligence
and what the future of intelligence
will look like for technology and business leaders, and we know that
organizations are paying attention. In fact, enterprises spent $200 billion on
data, analytics, and AI software, hardware, and services last year. That
doesn’t even include the investment in external data and internal labor costs
to further fuel intelligence initiatives.

IDC has been using the phrase “data intelligence software” to describe a category of capabilities that provide intelligence about data, and the term “data intelligence” has caught on in the industry. But not all definitions of data intelligence are equal. Let’s take a closer look at how IDC defines the term, and some permutations that have emerged.

Artificial intelligence (AI) is poised to transform the way that marketing professionals work, and how organizations target, engage and connect with customers and prospects. Just like how marketing automation created new tasks and job functions, AI will revolutionize the way marketing is performed – and dictate a new set of job needs and skills.

We’ve discussed how the term artificial intelligence (AI) covers a wide array of applications; just like many of these functionalities, affective computing is beginning to see some growth in the market. Spanning across computer science, behavioral psychology, and cognitive science, affective computing uses hardware and software to identify human feelings, behaviors, and cognitive states through the detection and analysis of facial, body language, biometric, verbal and/or vocal signals.