Artificial intelligence (AI) has become a notable buzzword across multiple industries in recent years. AI is so popular that the International Data Corporation expects global spending on AI systems will grow from $35.8 billion in 2019 to $79.2 billion in 2022. As leading tech companies continue to show interest in AI investment, users will continue to see the technology become increasingly integrated into more and more products and applications. While AI technology has seen useful adaptations in the healthcare, education, and finance sectors, it’s the mobile app development industry that provides 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 improve user satisfaction drastically.
This post will provide a high-level overview of the changing user demands and the application of AI in mobile apps.
In the simplest terms, AI is a system with the ability to copy intelligent behavior and make autonomous decisions. The technology is a branch of computer science in which computers are capable of performing tasks that typically require human intelligence; such as, situational or environmental analysis, problem-solving, reasoning, learning, and comprehending language, for example.
The McKinsey Global Institute separates AI into five broad categories: computer vision, natural language, virtual assistants, robotic process automation, and advanced machine learning. The research institute predicts that by 2030, 70 percent of companies might have adopted at least one type of the AI technologies listed above.
AI possibilities are endless, but within the context of mobile, it can be embedded using chatbots or in context-aware sensors. Many companies have already begun to build scalable AI strategies focused on creating value for their customers.
The expansion of AI technology has allowed mobile users to reposition the value benchmark of existing user experience altogether. Users are beginning to expect more in-depth and personalized mobile app performance.
By collecting and analyzing customer data based on purchases and locations, retail brands, including Starbucks, Tommy Hilfiger, and Nike can deliver personalized experiences that include recommendations unique to each user.
Co-Founder, and CTO of Clearbridge Mobile, Sanjay Malhotra points out, “The next set of applications will be a lot more intuitive and more interactive. The 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.”
We already see this with products like Tommy Hilfiger’s chatbot, for example. The chatbot allows users to browse their latest collections or get a behind-the-scenes look at the most recent fashion show. The chatbot also uses natural language processing not only to reply to customer queries but also offer style advice and product recommendations. By asking a series of questions, the bot gathers information about the user’s style preferences and makes an outfit suggestion based on the collected data.
Smartphones are equipped with GPS tracking, as well as microphone and camera features, making mobile the ideal platform for AI applications. Further, Apple revealed the iPhone XS, XS Max and XR will include an A12 Bionic chip featuring a neural engine built to utilize AI hardware in previously impossible ways. 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.
When it comes to voice-controlled assistants, Amazon is ahead of the competition. While Google is making strides in becoming compatible with more products, Amazon’s Alexa already integrates with a vast array of products like appliances.
Sanjay Malhotra also mentions 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 seamlessly and intuitively with natural everyday language. However, 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.
Google Home shines in areas of predictive and contextual computing. The Google assistant is capable of answering more questions than Alexa-enabled products. However, Amazon has the advantage of having a lot more developers on its side. It’s easy for third-party developers and device manufacturers to integrate Alexa skills into many applications.
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. The partnership 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.
Strategic partnerships have 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, customizing and streamlining the user experience.
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. The technology 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 use 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.
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 the 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 are causing a revolutionary shift in the way that developers, businesses, and users think about intelligent interactions within mobile applications.