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artificial intelligence

Development of Mobile Artificial Intelligence

Written by Sharon Rosa-Bohrer


Artificial intelligence (AI) is a term that used to conjure up the image of some futuristic, sci-fi computer-
driven technology, until Siri, Cortana, Alexa, and Google Assistant made AI mainstream. With human-like
capabilities and an advanced algorithm, AI offers better speed and reliability at a lower cost than human
counterparts. A 2016 survey by DemandBase found that 80% of B2B marketing executives believed that
AI technology would revolutionize the marketing industry by 2020. Artificial intelligence is the wave of
the future for mobile applications.
As our reliance on mobile technology continues to grow and feeds our need for mobile applications,
there is an amazing opportunity for artificial intelligence to help you grow your business. This
opportunity presents itself in four interrelated areas: mobile app development, marketing, app analytics
and mobile security.

Mobile App Development

Introducing AI into your app requires that your IT organization is able to secure mobile access to data,
ensure backend integration of apps with legacy systems and utilize API-based architectures. The payoff:
artificial intelligence enables you to understand user behavior on your app and to drive your marketing.
With AI’s automated reasoning (an area of computer science and mathematical logic), apps can be
programmed to “reason” for themselves without human intervention. AI analyzes the user’s actions in
the app and then tailors the user’s experience based on those behaviors. As technology advances, user
expectations for a personalized experience grow. To meet this need, AI can be used in mobile apps to
facilitate recommendation services that are based on users’ choices and preferences. Businesses must
strive to save their customers time and effort while delivering value. If your business can’t meet users’
needs, maybe your competitor can!

AI Drives Marketing

The best way to keep your customers satisfied is to provide them with relevant and engaging content
aligned with their likes and dislikes. By using AI and applying a learning algorithm to your app to monitor
user behavior patterns, marketers are able to personalize future app sessions with more relevant
content and features. Businesses can target their incentives to current consumers based on their
attitudes and where they are in the buying cycle. This makes your marketing efforts more effective and
80% of app users abandon apps within 90 days from the initial download. A main reason for this is the
app does not provide fresh, relevant, engaging content. This makes the first five app sessions critical for
retaining new customers. Content, whether in the form of push-notifications, emails, in-app messages,

blogs, etc., needs to deliver the right message, to the right user, at the right time, through the right
channel. We see the success that Netflix, Spotify, YouTube, and Amazon have with using AI to make
recommendations that meet their customers’ needs, enhancing the user experience and keeping them
coming back for more.

App Analytics

App analytics are the key to understanding how your mobile application works and what you can do to
improve it and attract new users or customers. Artificial intelligence plays an important role in app
analytics and uses both machine learning and predictive analytics to better understand the data being
collected. Machine learning gives your app the power to identify trends and increase accuracy and
efficiency over time. Predictive analytics leverage data in a way that allows you to make predictions and
anticipate a user’s actions, wants or needs. Sentiment analysis uses artificial intelligence to understand
the attitudes, opinions (positive, negative or neutral) and the emotions of customers. This
understanding, in turn, allows marketers to more precisely target their marketing efforts, incentives and
personalized offers to individual consumers.
App analytics enable you to monitor app performance across mobile, desktop and other device
applications. Businesses can then use these insights to make more informed, data-driven decisions.
By 2022, more than 50% of all enterprise mobile apps will use mobile analytics tools to improve the user
experience (Gartner).

Mobile Security

Approximately 80 billion devices will be connected to the internet and 180 zettabytes of digital data will
be generated worldwide by 2025, according to the International Data Corporation. Much of the vast
quantity of data that enterprise needs to protect comes from the increasing number of mobile devices
connected to the enterprise. These devices are connected to apps, websites, cloud services, and more,
making traditional cyber security tools insufficient.
The pattern-detecting algorithms of AI help detect some of these security holes. For example, AI enables
fraud detection for online payments by flagging “out-of-norm” purchases. However, while AI in mobile
security is continuing to develop it is recommended that AI be used to enhance existing cybersecurity
solutions and to build next-generation solutions.
AI is the wave of the future when it comes to mobile app development, marketing, analytics and
security. Many predict that business intelligence applications will be one of the fastest growing areas for
leveraging AI technology over the next five to 10 years.

Join Us!

Come to Mobile Payments Conference 2018, August 22-24 th in Chicago and learn from and network with
leaders in the Mobile Payments, FinTech and Cybersecurity industries!