8 key roles of successful AI projects

As enterprises further develop artificial intelligence projects, they are finding that some roles are essential to success. But the right talent can be hard to find.

8 key roles of successful AI projects
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Artificial intelligence offers ample opportunities to reap business value. When done right, AI can help improve sales, optimize operations, and free up staff for higher-value work. It can help reduce costs and empower organizations to create new products and pursue new markets.

And enterprises are diving in. According to a recent Deloitte survey, 55 percent of IT executives say their companies launched six or more AI-related pilot projects in 2018, up from 35 percent in 2017. More than a third have invested over $5 million in cognitive technologies, and 56 percent expect AI to transform their companies within the next three years.

But getting there isn't easy, and certain key skills are required — but hard to find. Here we take a look at eight key roles for AI success, according to those making early forays into artificial intelligence for business.

AI researchers

It might seem counterproductive for the average enterprise to get involved in research. After all, AI researchers are often the PhDs who perform fundamental research that could, someday, lead to a breakthrough in machines' abilities to think. Plus, going after AI researchers means competing against universities and tech giants like Google and Microsoft for near unicorns who might not immediately conjure business benefits.

But there's always hope that a breakthrough will catapult them into the lead. This promise alone may speak to the high demand for AI researchers. According to Deloitte’s survey, 30 percent of IT execs view finding AI researchers among their top priorities, more than any other role.

"People want that shiny object," says Vivek Katyal, global leader for analytics and data risk at Deloitte Risk and Financial Advisory. "But will that shiny object make a difference to what they're truly after?" Unless a company wants to be the next Facebook, he says, maybe not.

But many business executives making funding decisions don't understand the difference between AI research and AI applications, he says. "It's not the data scientists funding these projects."

For those companies where AI is critical to their core business, however, research is not a luxury, but a necessity. AppTek, for example, was founded around 30 years ago as a speech recognition company. The entire field of speech recognition has been transformed by AI, and AppTek has had to invest in research to keep up. For example, its latest published research focuses on identifying different speakers in a conversation.

"That's a real commercial need," says Mike Veronis, the company's chief revenue officer. "We did that to solve the problem, and to push capabilities."

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