AI faces the line between hype and promise

Questions hold on what's real, what's spin

Oracle co-founder and former CEO Larry Ellison once famously asked during a public event: “What the hell is cloud computing?”

Given that Oracle is and has been one of the most successful cloud companies in the world, he was obviously making a point about the widespread, unchecked rebranding he saw happening in the industry for technologies and products that had existed for decades prior to the arrival of the cloud hype machine. The tech industry is “the only industry more fashion-driven than women’s fashion,” Ellison said, and “cloud computing” or “something-as-a-service” was the newest trend.

“The interesting thing about cloud computing, it is either going to be or already is the most important computing architecture in the world, because we’ve redefined cloud computing to define everything that we currently do,” said Ellison with more than a hint of sarcasm. “I can’t think of anything that isn’t cloud computing.”

Much like how technology contractors began to use “cloud” as a marketing term for their existing offerings, there are signs that the market is beginning to frame its “artificial intelligence” offerings in the same light. Both technologies suffer from the disease of ambiguity, with uncertain or amorphous definitions that sometimes give sales and marketing departments wide latitude to rebrand their services to conform to the latest hot buzzword.

For an example of this phenomenon, read this story in Fortune from last year where Intel CEO Bryan Krzanich talks about their computer chip products (which they have been selling for years) by tying it to AI and presenting it as brand-new, cutting edge tech:

“It’s the same marketing speech he and Intel have been giving for the past few years, but what’s different now is that the company is heavily emphasizing ‘artificial intelligence’ as a catch all to what companies traditionally consider to be business or data analytics.”

In interviews with senior executives at five different technology contractors that provide artificial intelligence services to the government, each had a somewhat different internal definition of the tools and offerings that entail artificial intelligence.

Matthew Michelson, chief scientist at InferLink, said this widespread confusion is among his biggest “pet peeves” when discussing AI.

“People will often conflate different terms with AI, which is a pretty broad umbrella term, It encompasses lots of different stuff,” he said.

It’s not so much deception (all these technologies are compatible with and support artificial intelligence offerings) as it is a smart marketing and sales strategy. Though the definition is still being worked out and there is no consensus forecast, most market intelligence firms are predicting billions of dollars in exponential growth for the global AI market over the next five-to-10 years, with the United States emerging at the epicenter.

Before leaving office, the Obama administration released two reports on artificial intelligence and the effects it is expected to have on the U.S. economy. The final report released in December 2016 concluded that “AI-driven automation stands to transform the economy over the coming years and decades” and urged future administrations and the private sector to begin preparing for increased productivity, changes in necessary job skills and disruptions to the work force.

The latest push to recalibrate towards supporting AI in the contracting world is reflective of this reality. With everyone anticipating a massive shift across all levels of government in the next few decades, including automated or machine-learning components as compliments to or replacements of more traditional contract offerings can potentially give contractors a leg up when pitching to an agency purchasing office that wants to get ahead of the curve and prepare for an AI-centric future.

“You’re starting to see CEO’s ask ‘how do we get a competitive advantage in selling to the government? What’s going to make us competitive?’” said Matthew Carroll, CEO of Immuta. “I don’t think you will see AI-based contracts, but [rather contractors] utilizing machine learning as an additive when they go into procurement as a differentiator.”

The ability to automate low-level back office functions also carries the potential for significant cost-savings, giving established contractors even more incentive to jump into the burgeoning market through new products or rebranding of existing ones.

“I think there is going to be this increasing expectation that when government is acquiring services, it will be done in most cost effective manner,” said Steve Mills, principal director at Booz Allen Hamilton. “So I think as these technologies mature, governments will also require specific functions that are very AI-centric.”

About the Author

Derek B. Johnson is a former senior staff writer at FCW.

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