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How AI and ML are changing the landscape of app development


In order to survive in this competitive and digital world, companies are harnessing the power of apps to take their business to the next level. Over the past few years, Artificial Intelligence and Machine Learning have gained huge momentum across the Internet world. Earlier, usage of it was only limited to sci-fi movies, but now it has become an unavoidable part of today’s modern business. From talking with chatbots to gathering customer data to improve user experience, AI is today used by brands for various purposes.

Let’s consider the example of a well-known video streamlining site Netflix. Do you know how it works?

It basically collects user data and then recommends shows and series based on their preferences. This is how AI and ML works. Indeed, AI and ML have revolutionized the app development sector over the past several years with the use of:

  • Chatbots;
  • Predictive analysis; and
  • Smart sensors

Hence, AI and ML help brands to study user behavior and deliver a seamless user experience.

Also read: How to develop a location-based Augmented Reality app

AI and ML influencing app development

Today, Artificial Intelligence and Machine Learning are leaving a massive impact on businesses, society, and lives. We know that mobile apps have become an essential part of our lives. From ordering food to groceries to paying bills to call a handyman, the majority of tasks are performed by apps.

According to Harvard Business Review, AI offers a plethora of advantages to a business, by enhancing the performance of products to make better decisions to automate certain tasks. On the other hand, businesses are investing in feature-rich app solutions to grow their business reach and customer base. Today, mobile apps are the lifeblood of any business and act as the most vital medium for user engagement, customer service, communication, and accessibility of a business.

In order to improve user experience and brand recognition, more and more brands are now investing in AI and ML technologies. Still, confused? Let’s have a look at several stats that will help you understand the importance of AI and ML in app development.

  • The number of enterprises investing in AI and ML is estimated to double over the next five years;
  • 40% of US marketers use ML to improve their marketing strategies; and
  • 76% of companies have hiked their sales because of ML.

With the help of AI, mobile app development is changing. Besides, customer’s preferences are also changing, from fast checkout to product recommendations to round the clock customer service. AI contributes to app development in various ways like:

  • Making personalization better;
  • Better insights;
  • Security advancements; and
  • Product recommendation

Let’s discuss how AI and ML are transforming the app development industry with their advanced components and delivering extremely customized products to customers.

Also read: Smart Construction using Artificial Intelligence

Rise of Voice Assistant

Voice search is perhaps one of the most popular advancements in the AI field. Today, people often use voice search with digital assistants like Google Assistant, Siri and Alexa, and much more. According to Search Engine Watch’s research, voice-related searches are three times more than local text-based searches, and this ratio keeps increasing with time.

AI and ML-based virtual assistants and Chatbots are becoming popular in the business segments; business owners integrate them into their website and apps because it enables quick interaction with the user and saves time. Chatbots are changing the overall customer experience because they are bound to resolve customer queries, round the clock.

These apps offer several assisted services and also guide customers, solving their queries through chatbots. Chatbots in mobile apps enhance customer service and make 80% of tasks human-less. In turn, companies can ask human resources to focus on other core objectives. Many of us already have experienced chatbots when using any banking and eCommerce apps.

Use Case

Using its app, Bank of America customers can chat with the virtual assistant Erica either through text or voice commands. It enhances customer experience with the brand. Moreover, Erica also sends periodic messages to customers related to offerings and financial news.

Also read: Forecasting fire using satellite imagery, GIS and Machine Learning

Predictive Analysis

We all know how the usage of eCommerce and on-demand apps is increasing in our daily lives. Machine Learning helps marketers understand the choice and preferences of customers based on their browsing history.

Today, food business owners are using this feature to increase their sales. We are all aware of the fact that the food delivery market is booming, and that has increased the demand for online food ordering systems for restaurants as well because restaurants can collect the data of customers and later send them recommendations based on their search requests, location, preferences, and age.

AI and ML also help drive the personal recommendations and the advertisements that we see on apps.

Use Case

Amazon and food delivery app Zomato, using ML and AI that understands the customer’s behavior and sends them recommendations based on their likes.

Enhanced App Security

For any business owner, security is a significant concern, especially when it comes to an online business. There is a lot of sensitive customer data, and a security breach might ruin the brand image in seconds. But using Artificial Intelligence and Machine Learning during the development, businesses can improve the security of the app so it is capable of identifying threats before they arise. AI algorithms can detect malware and threats in real-time and help enterprises quickly prevent the threat.

As a result, more and more organizations are today adopting high-end AI and ML strategies to leverage the maximum potential from their apps while ensuring security. Similarly, marketers are also turning to AI and ML in order to better target a broad audience.

Also read: Using Machine Learning and Neural Networks for advanced space solutions

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