How Artificial Intelligence is Driving Mobile App Personalization
Artificial intelligence (AI) is rapidly becoming one of the most popular topics in both business and science and more leading tech companies are showing interest in AI investment. Google’s $400 million acquisition of DeepMind is a prime example of mainstream AI application. A study conducted by the Mckinsey Global Institute revealed that tech giants such as Baidu and Google spent between $20 billion to $30 billion on AI last year, with 90% of this spent on R&D and deployment, and 10% on AI acquisitions.
The rate at which AI is expanding is gaining momentum. The same study determined that AI expansion brought about three times as much investment in 2016 – nearly $40 billion – as it did only three years ago. Business sectors like healthcare, education, and finance are investing in AI, but mobile is one of the most promising areas for AI.
The idea of having a personal assistant to help tackle everyday tasks is attracting users everywhere. However, the potential for smart apps expands far beyond digital assistants. Today, mobile applications are using AI to drastically improve user satisfaction.
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? In the simplest terms, AI involves a machine with the ability to copy intelligent behavior.
AI is an umbrella term, encompassing capabilities such as machine learning, natural language processing, machine vision, and knowledge management.
AI possibilities are endless, 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 one of many tools to intuitively engage and ultimately retain their users.
Gartner predicts that intelligent apps were 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, every aspect of enterprise mobile apps will accommodate AI. In fact, Gartner anticipates 200 of the world’s largest companies will develop 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 explicit programming and can adapt 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.
Users are Demanding More Personal Experiences
The expansion of AI technology has allowed mobile users to completely reposition the value benchmark of existing user experience. Users are beginning to expect more in-depth and predictive mobile app performance.
In response to user expectations, Starbucks released their “My Starbucks Barista” mobile app at the beginning of the year. Users simply tell the app what they want, and it places the order for them.
Similarly, Taco Bell released “TacoBot,” which goes beyond automated ordering. “TacoBot” provides an enriched, tailored user experience by recommending personalized menu suggestions by anticipating user-specific purchase trends.
Sanjay Malhotra, Co-Founder and CTO of Clearbridge Mobile says, “The next set of applications will be a lot more intuitive and more interactive. A mobile experience has to be personalized and customized and what I see today is that it’s getting easier and easier to create those truly personalized experiences by leveraging AI and big data.”
AI-infused apps, or “smart apps” are growing in popularity among users as they conveniently help accomplish daily tasks.
Mobile is the ideal platform for AI applications. Devices are now offering a number of features to supplement AI performance. Smartphones are equipped with GPS tracking, as well as microphone and camera features. Further, Apple revealed the iPhone X, loaded with an A11 Bionic chip featuring a neural engine built for AI tasks such as Face ID’s 3D scanning. Combining AI technology with these built-in features makes apps more relevant and personalized. Using AI to contextualize user behavior will make each app session more valuable than the last.
Amazon’s Alexa is Setting New Standards
Even with competition like Google Home, Microsoft’s Cortana, and Samsung’s Viv, Amazon’s voice-controlled digital home assistant, Alexa, stole the show. The number of products with Alexa integrations announced during the event showcased Amazon’s dominance in this emerging market. Alexa has the potential to transform interactions between companies and their users with more than connected home devices.
Sanjay Malhotra also predicts that “Mobile and voice control will merge into a great user experience that will reduce the number of pain points users have. Smart home devices will do what they’re supposed to do as opposed to asking users what they should do.”
Voice interfaces allow users to interact with apps in a seamless and intuitive way with natural everyday language. But, it’s more than just voice recognition users want to see more of; users are seeking a variety of utility characteristics, 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 on their side. It’s easy for third-party developers and device manufacturers to integrate Alexa skills into a number of applications.
Alexa Pushing AI to Mobile
Alexa is dominating all competition because she has carved her own unique 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 has helped Alexa grow into a leading new digital platform, with the potential to become a central part of 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 like eBay and Amazon have already proved the success potential of AI mobile apps. With new advancements in technology and shifting consumer demands, AI mobile app development is the new digital frontier for enterprises.
The major tech companies are integrating these AI algorithms into various products to strategically secure 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 learned behavior. As we see more AI and machine learning-driven apps, businesses can leverage the data apps are collecting via point-of-sale machines, online traffic, mobile devices, and more to strategically improve the user experience. The algorithms will be able to sift through this data, finding trends and adjusting the apps themselves to create more meaningful and context-rich opportunities to engage users. Forward-thinking enterprises are capitalizing on the advantages AI provides as it continues to connect users to brands.
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 not to 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 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.
As a full service custom mobile app development company, Clearbridge Mobile handles the entire lifecycle of your product from Planning and Strategy, UX/UI Design, App Development, QA/User Acceptance Testing, to Technical Delivery. We use a unique agile development process that gives you control over scope, reduces your risk, and provides you predictable velocity. Start a conversation today to get started on your mobile project.