How Artificial Intelligence is Driving Mobile App Personalization
Artificial intelligence (AI) has increasingly become one of the hottest topics in both business and science. More leading tech companies are showing their interest in AI investment, from Google’s $400 million acquisition of DeepMind and Faraday Future’s unveiling of self-driving supercars at CES 2017. These are just a few examples of the commitment companies have towards this cutting-edge technology, but one of the most promising areas for AI is in mobile.
The idea of having a personal assistant to help tackle everyday tasks is becoming more appealing to users everywhere. However, intelligent apps are not just limited to digital assistants but for a variety of purposes from security to e-commerce. Today, many companies are applying AI in their mobile apps to transform the customer experience. This post will provide a high-level overview of the changing user demands and the application of AI in mobile apps.
The Basics: What is Artificial Intelligence?
The term “Artificial Intelligence” has been thrown around a lot recently, but what is it exactly? Fundamentally, it’s a machine or computer with the ability to solve problems that are usually done by humans using natural intelligence.
AI is an umbrella term, encompassing capabilities such as machine learning, natural language processing, machine vision, and knowledge management.
AI can be used for many purposes, but within the context of mobile, it can be embedded using chatbots or in context-aware sensors. Many companies are beginning to adopt artificial intelligence as a tool to deeply engage and ultimately retain their users.
Gartner predicts that intelligent apps will be one of the top ten strategic trends for 2017, more than just digital assistants that make it easy to complete common tasks such as prioritizing emails. Instead, intelligence will be built into every category of enterprise mobile apps. In fact, Gartner expects 200 of the largest companies in the world to have developed intelligent apps within the next year.
What’s the difference between AI, Machine Learning, and Deep Learning? Machine learning is a subset of artificial intelligence that provides computers with the ability to learn without being explicitly programmed and can change when exposed to new data. Deep learning is a branch of machine learning, based on a set of algorithms that attempt to model high-level concepts in data. Many recent AI experiments are relying on deep learning, which attempts to mimic the layers of neurons in the brain, creating an artificial neural network.
Users are Demanding More Personal Experiences
AI technologies are beginning to take hold in a variety of industries. Starbucks announced a new AI-powered mobile app called “My Starbucks Barista.” Users simply tell the app what they want, and it places the order for them. Similarly, Taco Bell released the TacoBot, which doesn’t just take orders, but also recommends menu items and answers questions. AI-infused apps, or “smart apps” are now being built to help users complete daily tasks.
What makes mobile an ideal platform for AI apps is the varying array of personalization capabilities. Smartphones are aware of user location and the outside world beyond the home, so integrating AI makes apps even more relevant and personalized. AI capabilities are being built into mobile apps of all kinds, making them contextually aware of user behavior. These technologies can be used to learn users’ behavioral patterns to make each app session more valuable than the last, increasing overall retention rates.
Amazon’s Alexa is Setting New Standards
Amazon’s voice-controlled home digital assistant stole the show this year at CES, competing against Google Home, Microsoft’s Cortana, and Samsung’s Viv, among others. The number of products with Alexa integrations announced during the event showcased Amazon’s dominance in this emerging market and demonstrated the potential that Alexa has to transform interactions between companies and their users in more than connected home devices.
Voice interfaces allow users to interact with apps in a seamless and intuitive way using natural everyday language. And it’s not just voice recognition that users are demanding but instead, a variety of utility functionalities, such as predictive messaging and context-aware computing.
While Google Home is capable of answering more questions than Alexa-enabled products, Amazon has the advantage of having a lot more developers building skills for Alexa. It’s now easy for third-party developers and device manufacturers to integrate using Alexa Skills. Skills is where Amazon is thriving, because they give Alexa the ability to be customized for any lifestyle on a variety of devices, making AI more accessible and mobile.
Alexa Pushing AI to Mobile
The main reason why Alexa is capturing the attention of millions and dominating competition is because she is carving her own space in the market. Amazon released Alexa in the home and is now transitioning her outside, contrary to her competitors. Ford has teamed up with Amazon to bring Alexa into its cars. This enables Ford users with SYNC 3 to access Alexa inside the car to do things like check the weather, play audiobooks, add items to shopping lists, and even control Alexa-enabled home devices.
This in turn has helped Alexa grow into a leading new digital platform, with the potential to become central to our day-to-day lives. This strategic move shows Amazon’s commitment to personalizing the user experience by bringing Alexa everywhere the user goes. We’ll begin to see more AI technology integrated within mobile apps, personalizing and streamlining the user experience.
How Will Mobile AI Impact Businesses?
Retail giants such as eBay and Amazon already proved the success of AI mobile apps. With new advancements in technology and shifting consumer demands, AI mobile app development is the next big thing for enterprises.
The major tech companies are integrating these AI algorithms into various products to strategically enmesh users further into their brand ecosystems. This helps businesses deeply engage users, providing more incentive to use their services, such as Amazon’s Prime delivery service that pairs well when using the Echo.
Many devices and applications will be written with algorithms that adjust based on observed behavior. As we see more AI and machine learning-driven apps, businesses can utilize the data that apps are collecting via point-of-sale machines, online traffic, mobile devices, and more. The algorithms will be able to sift through this data, finding trends and adjusting the apps themselves to create more meaningful and context-rich experiences. Forward thinking enterprises are capitalizing on the advantages AI provides as it connects users closer to brands, redefining the term, “personalization”.
Meeting User Expectations
Companies are quickly pursuing AI technologies however, technology has only come so far and has just grazed the surface of its true potential. Intelligence can be described as the ability to perceive information, and retain it as knowledge to be applied towards adaptive behaviors within a context so it’s important to not over-promise your products’ abilities. Users expect AI interfaces to learn and many fall short of true AI and deep learning.
New Opportunities For App Development
The growth of artificial intelligence is driving a whole new class of mobile app possibilities. AI has been heavily influential in app development for several years already, beginning with Apple’s Siri and it has potential to advance much more in the coming years. Machine learning has moved out of its infancy and users now want flexible algorithms for seamless and intuitive experiences. The new availability and advancement of AI and machine learning is causing a revolutionary shift in the way that developers, businesses, and users think about intelligent interactions within mobile applications.
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