Initially a puzzling discipline to all but the technological elite, in recent years it has opened its doors to innovators from a variety of industries who want to create more personalized disruptive technologies for the common consumer.
The aim of artificial intelligence is to have machines learn and deduct mass amounts of individual and collective data --and process through it quicker than a human brain would-- to give the user a truly personalized response. And because we are now the
most comfortable while chatting on social media or instant messaging apps, chatbots and AI-bots are becoming company’s choice delivery method for this type of highly- personalized and intelligent user experience.
We have accepted that soon, various parts of our lives will be ruled by machines gathering and analyzing large quantities of our seemingly insignificant data to provide us with the services we need or to steer us toward an outcome we desire.
But how exactly are AI and chatbots changing the consumer habits?
To delve further into our discussion on artificial intelligence, let’s take a closer look at a field having the potential to use AI and machine learning to offer its customers an experience beyond that of traditional methods. In recent years, the fitness industry has
been rapidly adapting to technological advancements. Companies that chose to develop smart fitness technologies for their customers are confident they’ll provide a better experience than their traditional counterparts. This is mainly due to a long history of disappointments associated with the long-established fitness industry.
An example of a smart fitness technology is Fitwell, an A.I. based app focused on providing holistic coaching combining fitness and wellness. It uses daily workout and diet information collected from its users and accordingly curates meals, tailors workout regimes. The app comes with a companion chatbot Hailee which is an A.I. bot that users can interact with Messenger or even talk to on Alexa or Google Assistant, asking it how many calories are in a bowl of cereal, for example, or, potentially, where would be the best place to go for a run on a Sunday. Coaching bots likeHailee, with the increase in their user data and advancements in technology will be able to even forecast the user behavior up to 100% and therefore improve the chances of success as a lifelong wellness companion.
As said, these products are not limiting themselves to current data. They are trying to push the boundaries and find ways to predict user behavior. Google recently launched its Pixel 2 phone. Their claim is that the phone is capable of knowing what the user needs before they, themselves, realize they need it, and with developments in Quantum Computing, this is no longer science fiction. Machines are now able to gather data that would normally be considered irrelevant to make predictions beyond human capabilities. Whatever the user’s technology of choice, these bots are ready to give a more personalized, on-the-go experience that would never be possible using traditional methods.
Spotify is a good example of how massive, communal data can influence machine behavior. Spotify’s song suggestions are normally based on individual users play history and preferences, but most users have a detectable tendency to prefer certain genres based on their preference of a specific song or genre. That is why Spotify uses machine learning to analyze community data to find patterns in their playlists preferences. Their system functions based on a combination of personal and collective algorithms. It’s not only your own preferences that are influencing the song suggestions you receive, but also the patterns of Spotify’s large number of users.
By using data collected over longer periods of time, these AI-powered gadgets are able to detect the slightest change of pace or preference and adapt quickly. While this type of data processing may not have huge consequences for a program like Spotify, they are beneficial in many other industries. Vi, a voice-activated, bio-sensing headset with machine learning capabilities, offers runners motivation and tips on the go. When the headset detects a decrease in your current performance compared to your previous data, it gives you immediate feedback and encouragement.
Chatbots, powered by machine learning, are tackling some of the greatest challenges that users face. In time, these machines will be able to collect and analyze even greater amounts of data and provide even more tailored experiences specific to each user. Perhaps the biggest claim smart apps and AI-bots can make is that sooner or later, they’ll know users better than they know themselves. For now, we will continue to track and observe how consumers are utilizing and benefiting from this technology. Only time will tell how successful bots will be in overtaking traditional industries.
Ilker Koksal, Contributor