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Gartner debunks 5 myths surrounding the AI hype

12 Sep 2017

Article by Gartner public relations director Christy Pettey 

Hype isn’t always a bad thing.

Within limits, it fosters attention, investment and innovation.

A little bit of hype can build excitement about potential, while too much leads to false hopes and misguided planning assumptions.

“Right now, the myths surrounding artificial intelligence (AI) are rampant,” says Alexander Linden, Gartner research vice president.

“Wisely, for now, most organisations’ commitments are tentative and more oriented toward experimenting and learning, rather than trying to transform their enterprise or industry as fast as they can.”

Enterprise architecture and technology innovation leaders must walk a fine line between embracing and overplaying AI technologies’ role in delivering business value for the digital business.

“Leaders shouldn’t trust any of the myths and hype around AI.

“Instead, they must become centres of expertise if they are going to educate senior business executives on the real benefits — and shortcomings — of AI,” says Linden.

Currently, plenty of myths surround AI.

Here are five of the top misconceptions:

Myth 1: Buy an AI to solve your problems

Reality: There is no such thing as “an AI.” Enterprises don’t need an “AI.” They need business results in which AI technologies may play a role.

“AI is a collection of technologies that can be used in applications, systems and solutions to add specific functional capabilities. Organisations should select best-fit, best-of-breed AI technologies to meet targeted business needs,” Linden says.

Myth 2: Everyone needs an AI strategy or a chief AI officer

Reality: AI is a loose collection of many technologies, and although they will become pervasive and increase in capabilities for the foreseeable future, focus instead on business results that these emerging technologies can enhance.

AI will affect all C-level roles.

Myth 3: Artificial intelligence is real

Reality: “AI” has become a generalised marketing term, often with little substance or value.

Very useful, specific functions have been created (such as speech and image recognition, game playing, fraud and failure prediction), but no general intelligence is in sight.

The concept of “intelligence” is an overrated generalization that leads to imprecise thinking. Be specific. Look for specific functional capabilities that drive the desired business result.

Myth 4: AI technologies define their own goals

Reality: People define goals; technologies execute them.

Technologies (whether AI or not) do not have their own goals that they seek to achieve.

Machines execute the programs they have been fed, whether the programs consist of code, data or both.

In AI, goal-seeking is an illusion programmed in by people.

Myth 5: AI has human characteristics

Reality: AI developers use advanced analytics, special algorithms and large bodies of data to deceive people into believing that their product learns on its own and understands, thinks and empathises with the user.

Management (and others) will continue to unconsciously anthropomorphize technologies.

Don’t be fooled into believing the technologies are more capable than they really are.

Investing under deceptive pretences can lead to unsatisfactory results and, worst case, career failures.

Article by Gartner public relations director Christy Pettey 

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