Mobile Apps without Artificial Intelligence? That’s so 2015!
Self-driving cars, game-playing AI systems beating the world’s best Go player, or virtual assistants in your pocket rightfully receive a lot of attention. These applications show major achievements in AI and outline a bright future for all of us. Artificial Intelligence is a hot topic at the moment. Always around, often mentioned, and hardly understood.
There are, however, traces of AI in lots of other domains and applications throughout the respective App Stores. Often unnoticed and thus not really recognized as advanced pieces of technology.
In fact it is believed that in the near future, some might argue that this future has already arrived, you will hardly find a successful app without an application of AI that at its core or least providing additional value for its users.
An obvious application of machine learning is to use the user data in order to make recommendations. In your favorite music player, like Apple, Google, Amazon Music, Spotify or any other service, tracking which songs you hear, which songs you tag, which songs you skip actually conveys a great deal of information about your preference or the current mood you are in.
It is a huge advantage if your music service is perceived to “understand” you, rather than being a mere storage that hold millions of songs. I once started a radio from a song on Google Music, a feature that picks the next song randomly based on your preference and the previous songs, and ended up listening to that playlist for days. An insurance has not (yet) given me a similar positive experience.
It is obviously more difficult for insurers to gain enough relevant data to make predictions since there is much less interaction with the user compared to a music service.
There are however, lots of sources of information that have hardly been used to improve the service to the customer and thus to generate revenue and improving customer retention. Whether it comes from smart home and IoT devices, social media or other freely available data sources on the web.
These sources of information may be used to predict customer behavior to prevent churn or to foster purchases, for image recognition to automate simple tasks, user segmentation for targeted campaigns, and many more. There is no limit to the ways we could make use of the customer data to gain insight and deliver more appropriate, better accepted services at the right time.
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An interesting study on the applications of AI in various domains:
