Artificial intelligence and machine learning have become vital to many aspects of financial services, from powering chatbots to improving fraud detection. But one area where AI has not gained as much traction, particularly with community financial institutions, is in sales and marketing. Its use has been steadily ramping up, though: SouthState Bank and Eglin Federal Credit Union are among those using AI to parse data in ways that have resulted in much greater impact for their marketing efforts. Rather than targeting people based on simple demographics like age or gender, they combine internal data with information available beyond their own databases to surface a much more telling -- read: predictive -- combination of details. The key benefit has been the ability to more accurately identify when customers are ready to buy a particular financial product and deliver the appropriate messaging to them.

Last November, Brookings published a report on artificial intelligence's impact on the workplace that immediately raised eyebrows. Many readers, journalists, and even experts were perplexed by the report's primary finding: that, for the most part, it is better-paid, better-educated white-collar workers who are most exposed to AI's potential economic disruption. This conclusion--by authors Mark Muro, Robert Maxim, and Jacob Whiton--seemed to fly in the face of the popular understanding of technology's future effects on workers. For years, we've been hearing about how these advancements will force mainly blue-collar, lower-income workers out of jobs, as robotics and technology slowly consume those industries. In an article about the November report, The Mercury News outlined this discrepancy: "The study released Wednesday by the Brookings Institution seems to contradict findings from previous studies--including Brookings' own--that showed lower-skilled workers will be most affected by robots and automation, which can involve AI."

Walt Disney World recently showed the Associated Press what it takes to put their shows together. It's a shift for a resort that hasn't allowed many peeks behind the curtains of the fantasy it creates. Maybe romantic Disney fairy tales come true after all. Data from the popular global online dating site Plenty of Fish reveals that singles who have expressed an interest in Disney are 3.6 times more likely to leave the app in a relationship compared to singles who more generally list interests in music and movies. That was certainly true for Disney fan Abby Schiller.

Among the multitude of new technologies entering banking's sphere, machine learning likely will quickly come to the fore. Imagine some poor bank employee sitting at a desk, peering at multiple computer screens. On those screens come waves and waves of charts, transaction lists, voice recordings, geographical data points, and social media posts, all constantly changing--and all focused on a single bank customer. The bank employee's job, at the moment: Decide whether that customer actually used his own credit card to buy a big screen television, or if that transaction, which just occurred, is fraudulent. And he only has a moment to decide.

These terms--just now coming into the banking vernacular--can be confusing, especially since they are all subsets of the equally dense term artificial intelligence or AI. It behooves bankers to make the effort to get a handle on what they mean, how they are interrelated, and, most important, what potential they offer to improve customer relationships, reduce fraud, beef up operational efficiency, reduce costs, and, ultimately, add to revenues. Through a number of interviews with Banking Exchange, bankers, analysts, and a prominent futurist paint a picture of what AI and its various subsets will mean to the banking industry. "AI is making it possible for customers to engage with companies in more ways than ever before through voice, gesture recognition, video, and chat, while opening up possibilities to serve customers beyond their own digital properties," says Brad Stewart, senior vice-president, head of product, AI Enterprise Solutions, at Wells Fargo. "We think these will continue to get even more sophisticated. Projects range from systems that can spot payments fraud or misconduct by employees, to technology that can make more personal recommendations on financial products to clients."