The fear of buyer's remorse is at play regarding artificial intelligence and its benefits. There’s plenty of research out there to say buying is the right decision. This information suggests AI is on the cutting edge of banking technology, and billions are being poured into research annually.
But none of that hype reassures most buyers. In fact, it makes them more apprehensive. Most can't help but wonder, "Is this AI system going to be obsolete in a year?" Many put off a purchase, figuring a delay will work to their advantage. After all, next year’s version is bound to be better, right?
And there is general buyer's remorse about any technology. My own memories can make me cagey about software purchases, especially in a professional setting where these decisions can have career impacts and judgments.
But that’s the funny thing about AI. Waiting is almost always a bad idea. That's because, unlike your new automobile or flatscreen TV, AI actually gets more valuable as it ages.
Why the inverse dynamic?
With most software, its capabilities are locked in the moment the code is complete. Try doing something the programmers didn't anticipate (like opening an unfamiliar file type), and the results can be ugly -- anything from an error message to an application crash. Applications mature, of course, and each new version (usually) works better than the previous one, but you have to constantly play the update game.
AI works differently. It can learn just about anything with few, if any, programmed rules. It can even learn from trial and error, the same way we
Let’s suppose you’re part of the KYC team at a bank, solving name- screening alerts generated by onboarding clients, and you work closely with an AI to do it. That AI investigates and makes decisions just like your best analysts (except a lot faster of course, solving over a million alerts per day). But no analyst is perfect right out of the gate, and smart as it is, the AI is no different.
The day it started, the AI was solving only around 40% of alerts without help, and after working at your side for a year, it’s up to 80%. How? The AI learns from every single case it sees. The longer it’s on the job, the more it learns — and the better it gets.
To use a nonbanking example, think about the recommendations social media makes for you. When I first signed up for Facebook, the paid content it suggested for me was laughably off base (like you, I’ve gotten political ads for politicians I'dnevervote for). But as time went by the recommendations became more focused, eventually narrowing in on things I actually did find interesting. Sure, there are still some weird items that come up in my social media feed, but now they're the exception rather than the rule.
So why buy an AI system now, rather than waiting two years? Because a system with two years of learning under its belt will do the job far better than a new one that has to learn everything from scratch. It's the same reason that someone who's been with your institution for two years works more efficiently than a newly hired employee. Experience matters.
The fact is, it’s only the banks that have learned not to think of AI like an old-school software product, and regard it instead as an extremely skilled and eager-to-learn employee, that are truly tapping the enormous potential of this powerful new technology.
The two big investments that a bank makes in AI are money and time. You might be tempted to wait to make a purchase, because you believe it will save money. But really, you're just losing time.
