Artificial IntelligenceContributorsData Science

AI Is Disrupting Everything And These 3 Industries Are Next

You may not see it, but it’s there. Artificial intelligence, that is. It’s beating us at our most complicated games, helping curate the news we read every day, ever improving our search results, driving our cars, and on and on and on. We’ve entered into what some experts are calling an AI spring, a thawing of the barriers that have previously prevented AI practitioners from achieving the breakthroughs we’re seeing today (namely, access to data, low-cost compute power, and better AI algorithms).

With massive investment and momentum in the space, it’s a simple fact we’re going to see AI’s fingers in a lot of pies over the coming decade. Plenty of industries will see quantum or step-function improvement…but some more than others. Here are three that are uniquely positioned to take advantage of the accelerating advances in AI.

Retail

When you get right down to it, not a lot has changed in online retail over the past decade or so.  We have more options–for shipping, how to pay, and in products–but the fundamental experience of shopping online is basically the same as it was when e-commerce started: you search, you filter, you add to cart, and you buy. You might view e-commerce as a tremendous success, given the growth we’ve seen. But, equally arguably, e-commerce has been a failure, with 3% conversion rates compared to the 17% we see in brick and mortar stores.

AI, however, may be poised to level the playing field between online and physical retail. You’re already seeing retailers like Amazon embracing AI  in their products (Echo, namely) and also to optimize the complicated universe of supply chain logistics and customer demand. This is happening as we speak, but like a lot of artificial intelligence uses, it’s happening in the background, more or less unnoticed by consumers.

Looking for AI implementations users we can actually see? Start with chatbots. Chatbots use various AI-based natural language processing (NLP) algorithms that can mimic human speech and help users complete orders, book travel, find products…you name it. In retail, chatbots are already helping shoppers on Sephora and H&M find products they want, and those brands are far from outliers.

In essence, chatbots try to solve for one of the main advantages brick-and-mortar stores have over their online cousins: the personal touch. A great salesperson, after all, can be the difference between a shopper buying and a shopper leaving. A good chatbot can answer some of the common questions individual shoppers have, guiding them to product choices, spelling out deals and offers, and generally making shopping seem more like a conversation and less like interacting with a giant searchable database.

But chatbots are just the start. In fact, other technologies solve for personalization more subtly and with less burden on the user: smart AIs can also transform user clickstreams into virtual personal shopping assistants, all in a few interactions. Basically, it works like this: A user clicks on a product they’re interested in and the AI can suggest a few other, similar options. Once the user chooses to explore one of those options, the AI starts to intuit that customer’s personal style on the visual similarities between the products this user is interested in, eventually paring down entire catalogs into a few choices that are closest to what a shopper is actually looking for. Just like a good salesperson would.

Healthcare

Another industry benefitting in a huge way from AI is healthcare. And the results will save lives.

Artificial intelligence traffics in massive amounts of data, and few fields collect as much data as healthcare. For example, there are millions upon millions of published medical papers. It’s unreasonable to expect any medical professional to be up to date on the state of the art with that much data coming in. This can make diagnosis difficult, especially for the thousands of rare diseases that most doctors simply haven’t heard of.

But treatment and diagnoses are great use cases for healthcare AIs. In fact, one took about ten minutes to find a better treatment for a patient suffering with leukemia. Keep in mind: it’s not that AIs are replacing doctors here. Far from it. Here, you see AIs augmenting human expertise, curating millions of pages of human thought and finding the right match for a patient in need. This is something we’ll see more and more in the future.

And again, that’s just a single use case. Using typically available data from operating rooms, Sentient partnered with MIT to predict the onset of sepsis–the leading killer in the ICU–with a success rate above 90%, giving ICU doctors and nurses the ability to act quickly to prevent this killer. Radiology scans and other diagnostic imaging will see positive disruption from injections of AI. Same with follow-up care, health insurance and health records, drug design, research: the list, essentially, is endless.

Finance

New technologies are often adopted by financial markets first, given the sheer scale of the industry and their ability to invest in them. AI is no different. Finance has used AI algorithms for a long time to compute credit scores and identify fraud, and now we are again seeing chatbot-esque approaches, this time to help banks answer customer questions more quickly.

And then there are the financial markets themselves. Robo-trading has been around long before our current AI spring, but these robots were less “intelligent” than they were fast–speed trading based on computational power. Artificial intelligence in the markets means actually using hypotheses and strategies created by AI to make trades with real money. And, yes, it’s happening all over the world. Everything from AI acting as your personal stockbroker to artificial intelligence finding stock predictors to AI running entire hedge funds: it’s all here, right now.

These are just three industries among many that will be disrupted by artificial intelligence. But what ties these three together is notable. They all create massive amounts of data that a team of data scientists (or, for that matter customer service representatives) would have an impossible time dealing with. But within that data, there is space for real decision-making that can improve processes, make for happier customers, and positively affect the bottom line for companies smart enough to jump on sooner rather than later.

Because make no mistake: AI has already taken root in countless industries. It’s only a matter of time before it’s truly ubiquitous.

 

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Image: photosteve101, CC BY 2.0

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