Be honest, you devoured all of Arnold Schwarzenegger’s Terminator movies. You bit off your nails during the first installments of the series as the Terminator decimated every organic creature crossing his path. Later, the robotic beast showed you his softer side, caring for the same people he’d previously hunted. You loved all of it. Infused with buttered popcorn and litres of pop, you may have binge watched the whole series in a day, tracing Arnold’s AI evolution from laser-sighted monster to bionic teddy bear. The Terminator really grew on you, didn’t he?

I suspect many folks on the planet view artificial intelligence (AI) as the exclusive domain of Hollywood’s feature films. If movies provide your baseline for understanding AI, you may be convinced that AI will arrive far into the future with both tremendous upside and the potential for untold carnage. However, there’s a noticeable, real-time buzz about AI – you see AI startups popping up everywhere and filling the tech start up ecosystem, not to mention hearing about it frequently in the corporate community. Why all the buzz? Artificial intelligence’s deployment in business – what many of us are calling cognified enterprise – is poised to reshape how we do what we do. From data curation to voice response technologies that learn with every tick of the clock, AI will not only influence the work of my colleagues in technology but will eventually impact the goings and comings of every consumer on the planet. Bank on it.

Fueling the Innovation

As I write this piece, there’s tremendous AI hype on the venture capital side of the market. From advanced robotics to cloud-based processes, startups galore trumpet the potential of their AI product. Of course, the robust fanfare also signals the need for startup capital. In the past, investors and evaluators could dissect the claims of startups by assessing market trends, existing products, and the white paper of the innovation the startup was proposing to offer. This is not the case with AI as there is no previous AI experience to draw from as product evaluations unfold. I suspect my forbearers at IBM faced the same capital crunch when they marketed punch cards and card readers over a century ago. What is this and what can it do for us? While many believe that there’s a certain risk involved in investing in cognified enterprise and the AI technologies that will support it, I am certain that many investors and existing corporations will take the plunge and participate in the movement. I, for one, prefer to ride the leading edge of the wave rather than tread in its wake.

The Possibilities

Stepping beyond the hype, one can see some imminent and legitimate uses of deployed AI technologies and software. Consider the voice response products many of us use daily. While “Siri” may be able to get us from Detroit to Vancouver when we ask “her” for a map, she has nothing to say when we request a route that avoids “sketchy backroads” and the “Popo,” (that is slang for the police I learned long ago from one of my longest time friends, now a sergeant). I’m sorry, I didn’t understand you. An AI version of Siri could have the ability to “learn us” and our use of slang, recognizing that our tongue and cheek references to law enforcement and forgotten highways is code for “get me where I want to go in the most efficient manner possible.” Imagine a Super Siri in the office space equipped with the ability to decipher our mannerisms, decode our sarcastic comments, and lighten the load. Jim, you seem a little stressed this morning…how I can make your job easier?

I’m buying, what about you?

And then there’s data. Every business amasses data. IBM knew this in 1911 and saw an opening to make data curation a hell of lot easier. From medical files to clicks of a turnstile at an entrance to a business, organizations are often awash in a flood of data. How could AI help us with all this amassed information? She could cull through it for relevance. If an AI system can determine the subjective value of the data relative to the objectives of the business and then organize and present the data to the team in the office, then they have more time to spend on customer interactions and product development and innovation. Think of what this means…doing less administrative activities and more value-based work, more time to interact and explore – – increased satisfaction – greater engagement. Happy employees = happy customers.

Be an Optimist

While we must be discerning business leaders as we evaluate the claims of the all the startups lauding the next big thing in AI, I’m quite simply banking on AI as a whole. The Terminator (kinder gentler version) is not walking through the door in a suit and tie next Tuesday, but the transformative AI opportunities are much closer than we all think (and not just those developing the solutions within the great blue walls I work). Within the next decade or sooner, AI will undoubtedly be the workhorse behind many of our organizations’ data curation operations. Looking out a bit further – but not too far – a “Super Siri” may be placing a mobile Starbucks order for us, “sensing” that the office staff could use s caffeine boost as they pull an all-nighter. I’ll take a (keto) pumpkin spice latte with that order!