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Embedding Artificial Intelligence in Mobile Apps

Artificial Intelligence in mobile apps offers new ways to improve user experiences, make apps more powerful business tools and reduce churn. Here's practical advice to get started.

Embedding artificial Intelligence in mobile apps offers new ways to improve user experiences, make apps more powerful business tools and reduce churn. Here's practical advice to get started.

The vast majority of business apps use databases. Our customers frequently integrate with Microsoft SQL, NoSQL, SQLite, Oracle, SAP and more. Recently, CIOs we speak with have started talking about the rise of artificial intelligence as a data source, and they're beginning to look at how to embed artificial intelligence in mobile applications.

We’re written recently about chatbots and sensors becoming key to mobile app development. At the recent MIT CIO Symposium, CIOs were talking to us about AI technology and machine learning. As CIOs, IT leaders and developers begin to consider how to build AI powered apps, here are two articles we thought our readers would find particularly helpful.

First, Janakiram & Associates Analyst Janakiram MSV recently wrote an article on 3 Steps to Embedding Artificial Intelligence in Enterprise Applications. The article stressed the importance of developers to build a roadmap to intelligent business apps for mobile devices, and offered practical advice developers could start using today.
"Artificial Intelligence is all set to become the new database for the next generation applications.”
He predicts:

“Like databases, Artificial Intelligence (AI) is moving towards becoming a core component of modern applications. In the coming months, almost every application that we use will depend on some form of AI....Artificial Intelligence is all set to become the new database for the next generation applications.”

In his article, Janakiram outlines 3 steps developers can take to begin polishing their knowledge of AI for app development and bring AI features into their apps::

1. Start Consuming Artificial Intelligence APIs Janakiram explains that this is the least disruptive way to get started – by turning existing apps intelligent by integrating with APIs for text-to-speed, speech-to-text, natural language processing, video search, language understanding, image processing and more. He includes a sample list of Artificial Intelligence Platforms that expose their APIs at an affordable price point:

2.  Build and Deploy Custom AI Models in the Cloud Once companies start consuming APIs, they’ll want to move to the next level – that’s where companies will want to acquire data from a variety of corporate sources and implement custom machine learning models that utilize a data engineering or data science team.

He suggests that Machine Learning as a Service (MLaaS) offerings can take the data and expose the final model as an API endpoint (similar to how Platform as a Service (PaaS) offerings, like Alpha Anywhere, take code and scale it in the production environment). He provides a list of MLaaS platforms developers should consider if they’re ready for this step:

3. Step 3 – Run Open Source AI Platforms On-Premises

4. Finally, Janakiram lists open source platforms for Machine Learning and Deep Learning that developers should begin exploring to get into more sophisticated artificial intelligence efforts:

In a second piece by AI vendor Neura, writers proposed 6 ways developers can start embedding artificial intelligence into their apps to improve user experiences:

  1. Moment Based Alerts – typically, alerts are based on the clock, but AI generates alerts or reminder based on the user’s context or real-time activities.
  2. Tailored Messages – apps can generate intelligent, personalized messages based on behaviors that are captured and analyzed
  3. Self-Knowledge/Awareness – apps that capture behaviors can then tell users more about themselves, their physical trends and prompt action or in-app behavior
  4. Proactive Service – smart apps that have proactive services take action based on a user’s behavior, such as turning off a thermostat or lights when a user leave the house.
  5. Smart Logins – who isn’t frustrated with login processes? Getting users into and out of systems as needed, or as required by security or safety requirements, can make for better user experiences.
  6. Next-Level Gamification and Incentives – apps that can assess user behavior and reward them -- or encourage them - to take action, can help make apps a fun, routine part of the day.

Artificial Intelligence offers many new ways developers can improve user interfaces, make apps more powerful business tools and reduce churn. Alpha Software is one of the mobile app development companies at the forefront of mobile app innovations and AI applications. We're helping companies deliver apps with virtual assistants, voice recognition, voice search, advanced search engine capabilities, text message notifications and more.

We’ve recently written about why Artificial Intelligence is the next big thing in mobile We’re pleased to share this additional advice to developers so they start on the path of building tomorrow’s intelligent apps. Read how AI will be further fueled by cheaper sensors Read what Gartner believes the top 200 companies will do with Artificial Intelligence by 2018

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Read Janakiram MSV’s article3 Steps to Embedding Artificial Intelligence in Enterprise Applications or Neuva’s article Avoiding Churn with AI: Six Ways to Boost Engagement of Your IoT Device or App with Artificial Intelligence

Artificial Intelligence: The Next Big Thing in Mobile
How to Set Up a Mobile Center of Excellence

About Author

Amy Groden-Morrison
Amy Groden-Morrison

Amy Groden-Morrison has served more than 15 years in marketing communications leadership roles at companies such as TIBCO Software, RSA Security and Ziff-Davis. Most recently she was responsible for developing marketing programs that helped achieve 30%+ annual growth rate for analytics products at a $1Bil, NASDAQ-listed business integration Software Company. Her past accomplishments include establishing the first co-branded technology program with CNN, launching an events company on the NYSE, rebranding a NASDAQ-listed company amid a crisis, and positioning and marketing a Boston-area startup for successful acquisition. Amy currently serves as a Healthbox Accelerator Program Mentor, Marketing Committee Lead for the MIT Enterprise Forum of Cambridge Launch Smart Clinics, and on the organizing team for Boston TechJam. She holds an MBA from Northeastern University.

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The Alpha platform is the only unified mobile and web app development and deployment environment with distinct “no-code” and “low-code” components. Using the Alpha TransForm no-code product, business users and developers can take full advantage of all the capabilities of the smartphone to turn any form into a mobile app in minutes, and power users can add advanced app functionality with Alpha TransForm's built-in programming language. IT developers can use the Alpha Anywhere low-code environment to develop complex web or mobile business apps from scratch, integrate data with existing systems of record and workflows (including data collected via Alpha TransForm), and add additional security or authentication requirements to protect corporate data.