There’s a simple reason behind the explosive growth of mobile-app ecosystems: with a good idea, a solid development team, and a bit of luck, tech pros can make a lot of money off building apps for businesses and consumers.
So as the tech giants shift their focus from mobile devices to artificial intelligence (A.I.) and machine learning, the inevitable question arises: how can developers—always on the lookout for the next big thing—get paid to develop new A.I. products?
The central challenge is format. A mobile app (and most software, for that matter) is a discrete unit, no different than any other product. You can charge for it up-front or give it away for free; you can institute subscription tiers that force users to pay for different levels of functionality. Whatever the monetary structure selected, the fundamentals are pretty clear-cut.
With artificial intelligence, however, things are a bit… wigglier. Google, Amazon, Apple, and other firms are baking A.I. and machine learning right into the interfaces of their latest hardware products. Developers can use those firms’ APIs to build functionality and “skills,” but how can they monetize all that effort?
Amazon has a new program that could turn into a robust payment channel for third-party developers. “Starting May 2017, we are offering game skill developers the opportunity to earn money based on customer usage,” the e-commerce giant wrote in a note on its developer site. “Customer usage could be measured using a variety of metrics, such as minutes of usage, new customers, and other measures of engagement.” (A “game skill” is one categorized in Alexa’s ‘Games, Trivia, & Accessories’ category.)
According to TechCrunch, some developers are already seeing some cash from Amazon—one unnamed tech pro forwarded an email showing that ‘Math Mania’ (one of the top-performing game skills on Alexa) had paid out $133.84.
The big question is when Amazon will expand its payments beyond “game skills”—and if its rivals will launch similar programs. For tech giants, developer payouts—even small ones—could spark A.I. platforms’ rapid growth. But as with the early years of mobile apps, companies and developers will need to engage in a lot of experimentation to figure out what works, as well as ideal price-points.
Digital assistants aren’t the only A.I. playing field. Chatbots are also on the rise, despite some early debate about their effectiveness. The technology is still nascent, but it’s easy to envision a near future in which companies offer chatbots-as-a-service; clients would pay for a bot to handle various tasks. If you’re a developer, knowing how to build e-commerce or customer-service bots that are actually capable of completing goals could make you a valuable commodity.
Fortunately, there are already a handful of toolkits for those interested in building bots, including Facebook’s developer platform (for anyone who wants to build bots for Facebook Messenger) and Botkit. This article in Entrepreneur breaks down other bot-builders, some of which are quite specialized.
Constructing an effective (and profitable) bot is about more than coding; you also need to understand user psychology. Some early efforts at chatbots failed because the final product was annoying or “spammy.” If users quickly get frustrated with your bot’s interactions, they simply won’t deal with it.
Mobile Apps 2.0
Artificial intelligence could end up having a sizable impact on mobile app UX. Imagine apps that are more capable of anticipating user needs, for example. Updating an existing app with additional A.I. and machine-learning capabilities could open up a channel to monetization in the form of subscription services, add-ons, and more.