In a recent LinkedIn survey, I asked product and software developers if and how they were making their software smarter. A surprising 57% cited A/B testing, while another 50% reported they were still swinging from decision trees.
Why are developers still solving everyday pain points with these manual, archaic processes, as opposed to employing “Little AI”? There are millions of everyday use cases for AI, where technology is empowered to learn and decide on a course of action that offers the best outcome for consumers and companies alike. The problem is that the Big AI we’re used to has a lot of challenges that make it inaccessible for developers to employ for tasks that’d benefit from everyday AI.
What we’re missing
Take this article you’re reading right now. If TechCrunch let loose a Little AI – essentially empowered machine learning – it could learn you prefer to read short, newsworthy articles in the morning and longer thought pieces at night. That learning informs a personalized home page, presenting you with bullet points upon awakening and feature stories at night – all without you having to laboriously enter your preferences or respond to pop-up surveys.
Little AI also learns that what your VC friend wants to see on their screen first thing is recent series funding announcements. A truly personalized experience is not only our expectation, it is the core component of the relationship between us and our content providers. And yet, it’s missing.
Let’s raise the stakes. There are multiple players in the split-pay space. A sprinkle of Little AI can teach a fintech provider that one consumer likes to finish paying off an item in less than six months and never wants any outstanding payment to exceed $250. It can also learn that they are open to revolving credit/product offers for an experience-related purchase above $1,500. This type of truly personalized financing enables both the consumer and merchant to benefit from a completed sale while lowering the risk of default to the credit provider.
Travel will be coming back in a big way, with more deals than ever. Little AI can jump in and learn how to make that experience far easier for consumers and far more successful for travel providers. Rather than showing consumers every single deal for every single location, it can take personal preferences into account.
