Why AI Needs to Vary by Industry

AI ImageAs organizations in every industry seem to be in a race to make artificial intelligence (AI) as realistic as possible, I would argue those “human-like” features aren’t necessary to the evolution of automating customer services and interactions in every field — and it might not be what consumers ultimately want.

The primary difference comes down to the way AI is leveraged differently by vertical market. Healthcare and banking in particular are great examples of the various ways AI can improve engagement based on the specific needs of an industry.

Following is an excerpt from my recent article in The Financial Brand on the different ways AI should be approached in banking vs. healthcare: Most Financial Institutions Over-Engineer Their AI Solutions. It’s time to change the type of AI conversations we’re having to ensure certain industries aren’t held back in the process.

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As healthcare and banking digitally transform, there seems to be a hesitation around leveraging AI technology unless it meets the Turing Test. However, the speed of transformation and the public’s demand for always-available services require the help of automation now — not 20 years from now, or even 5 years from now. Banking is a good example.

While healthcare patients may certainly want an AI system with a good bedside manner — after all, that field can involve some difficult conversations — banking customers are not looking for the same level of human-like interaction or sensitivity. Where healthcare is a highly emotive space, made up of personal comfort levels and preferences, banking is largely transaction-based and relatively constant based on demographic. Yet even in healthcare, non-humanistic AI is helping nurses spend more time where it truly matters (i.e., with patients) by allowing them to step away from the appointment scheduling process, unless absolutely necessary.

This is why it’s so important for each field to individually assess how and where AI fits into their ongoing digital transformation — long before it’s sophisticated enough to rival human contact. Because the expectation for speed and availability is already there, if AI as an automation tool is ignored in the short-term, it risks stunting the long-term evolution of those industries.

For example, communicating with one’s bank in order to proceed with various types of transactions doesn’t require an AI-based messaging system that could level a peace treaty — it just needs to be able to interact and make recommendations or transfers based on the customer’s immediate need. And those needs remain largely the same regardless of demographic. A middle-aged customer in Wichita, Kan., for example, who owns a farm and is married with three kids uses the local bank for basically the same purposes as a young, single professional living in New York City. Banking, by-and-large, is made up of the same types of interactions regardless of who or where you are: withdrawals, deposits and transfers. As a result, the faster those interactions can be completed, the better.

This is important because banks today are even competing with consumers themselves, leveraging peer-to-peer, mobile payment services such as Venmo to transfer funds directly to friends and family without going through a bank. In healthcare, AI would obviously need to look different because, as a general field, its care is highly individualized. However, in the end, both industries are doing all they can to ensure that patients and customers feel well-cared-for the same way retailers and hotels do; it just looks different. AI is not a one-size-fits-all solution, but it also can’t be ignored in its simpler forms.

It’s time to debunk the myth that human-like AI is the only answer to the ultra-connected world of tomorrow, because it could risk holding back certain industries if they refuse to implement it in any other form.

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