Artificial Intelligence and App Development Will Help Fill the Mobile Development Talent Gap

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Artificial Intelligence and App Development Will Help Fill the Mobile Development Talent Gap

New Gartner research predicts that artificial intelligence and app development will come together as application development teams will augment their efforts with artificial intelligence co-developers to streamline programming and meet business demand.

New Gartner research predicts that artificial intelligence and app development will come together as application development teams will augment their efforts with artificial intelligence co-developers to streamline programming and meet business demand.
New Gartner research predicts that artificial intelligence and app development will come together as application development teams will augment their efforts with artificial intelligence co-developers to streamline programming and meet business demand.

It’s no secret that enterprises are having a difficult time meeting internal demand for building apps, including mobile apps. The Gartner report, “Survey Analysis: The Mobile App Development Trends That Will Impact Your Enterprise in 2017,” found that “More than a quarter of enterprises globally have not built, customized or virtualized any mobile apps in the last 12 months.” The report also found that enterprises that have developed mobile apps have deployed, on average, eight mobile apps to date. On average, respondents say they are currently developing 2.6 mobile apps, and are planning to develop 6.2 enterprise mobile apps in the next year, but don’t yet have them under development.

A new Gartner report, “Predicts 2018: Application Development” finds that help is on the way from an unlikely source — the combination of artificial intelligence and app development. The report says: “To keep pace with the demands of digital transformation initiatives, application development (AD) teams will augment their efforts with artificial intelligence (AI) ‘co-developers’ to streamline programming efforts.” In addition, artificial intelligence and machine learning will help with quality assurance, agile product management, and cleansing and organizing data.

At the beginning, the report says, artificial intelligence co-developers will handle low-level, mundane tasks like infrastructure and other “plumbing” tasks, “to enable developers to concentrate on design and programming tasks more tightly aligned with business logic.” But that will change over time. Gradually, artificial intelligence co-developers will take on much higher-level work, “and emerge as peer reviewers and experts in specialized development tasks.” By 2022, the report concludes, “at least 40% of new AD projects will have virtual artificial intelligence co-developers on their team.”

Artificial intelligence and app development, the report goes on to say, will eventually use machine learning “to automate code preparation, validation and generation.”  That will free designers and programmers to spend more time on difficult problems related to business value, rather than on coding.

Artificial intelligence (AI) will also be used increasingly for app testing, the report says. In fact, it concludes, “By the end of 2019, AI-enabled test set optimizers will be in use at 70% of global platform-as-a-service vendors.”

Alpha Software will remain a powerful tool even as artificial intelligence co-developers begin to be used by enterprises. Its low-code approach to app development allows developers to quickly design apps and test and iterate them, exactly the kind of high-level tasks that programmers will do more of.

For more about artificial intelligence and app development, read my blog post, “Artificial Intelligence: The Next Big Thing in Mobile" or download our comprehensive artificial intelligence and app development whitepaper ("Artificial Intelligence: What You Need to Know About the Next Big Boom in Mobile"), which covers:

  • market data, processor advancements and sensor production advancements that have made artificial intelligence-powered mobile apps an everyday reality..
  • practical examples of how companies are leveraging AI and machine learning with input from sensors to power better business apps.
  • an actionable list developers can follow to start embedding AI into their apps to improve user experiences and decrease churn.
  • 3 steps, with detailed links to resources, that developers can take to begin polishing their knowledge of AI technology and AI APIs for app development.

You can also read through some examples of how the oil and gas industry will benefit from the combination of artificial intelligence and mobile development.

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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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