Mobile applications are increasingly redefining how people connect, communicate, and work. As consumers and professionals, they now demand applications that can support and streamline how they create or add value at work and home. Over the past decade, there has been a dramatic rise in the demand for custom Android app development; the pandemic accelerated the demand to the next level.
To meet the increased demand for applications, solutions architects and software engineering are increasingly exploring new and innovative technologies that can help them elevate their productivity and accelerate their time to market. That’s where Artificial intelligence (AI) and machine learning (ML) appear on the surface. In this blog post, we will explore the role of AI and ML technology in custom Android app development.
Meaningful interactions and experiences that drive business revenue
Today’s customers demand highly personalized content from the apps they subscribe to or use daily. By leveraging AI and ML solutions in the custom Android app development lifecycle, software engineers can build apps that can successfully track user behavior, preferences, and choices of the end users and leverage that data and insight to deliver personalized content, recommendations, and offers.
Take an ecommerce app, for example; it keeps a tab on the shopping habits of its users, how they shop, what they shop, when they shop, and what they save in their wish lists, and generate insight based on all of this data; this insight then drives the app to provide customized product and service offers that customers can relate with and will be more likely to buy from the app. This level of customization in experience and offerings improves user engagement and helps improve business revenue.
Predictive analytics to stay prepared for the future
Predictive analytics can help a business succeed in the face of uncertainties. AI and ML technology can help today’s companies capture and analyze data about their customers, business processes, vendors, and more. This massive amount of data can then be analyzed to predict the opportunities and threats that can unfold themselves in the future and find and develop ways to address them effectively.
NLP to build apps that understand and interpret human language
Natural language processing (NLP) is a branch of Artificial Intelligence that empowers computer systems to understand and interpret human language. In a short span of time, this AI technology is driving hundreds of programs or applications. In custom application development, software developers can leverage NLP technology to build a range of applications; for example, NLP can be integrated into a language learning app that needs to understand a user’s speech and provide real-time feedback on pronunciation accuracy and grammar. A custom Android app development company can also use NLP to build or enhance a chatbox to understand and respond to common customer queries in natural language.
Image and Object Recognition to build powerful applications
AI and deep learning algorithms can take app development or intelligence to another level. By integrating these intelligent technologies into the application, designers and developers can create next-generation applications that can identify and classify images and objects in real-time and help the user make the right decisions. For example, deep learning technology can be used to develop apps to track objects, vehicle detection, and across manufacturing, healthcare, and the military.
Frameworks and platforms for AI/ML integration
Digital application development companies tap into multiple tools and frameworks to speed up development and reduce market-to-time for their customers. A tool or Android app development framework significantly reduces the need for the developer to start development from scratch. The frameworks accelerate the development process and ensure applications conform to the highest quality standards and look great on their intended screens and devices.
Software engineers can leverage frameworks and APIs like PyTorch, TensorFlow, and Keras to integrate AI and ML capabilities or features into applications. Besides, platforms like Google Cloud AI, AWS AI, and Azure AI also offer pre-built AI models and APIs. Using these frameworks and platforms makes it easier for developers to harness the power of AI and ML into their applications.
The bottom line
Intelligent technologies, such as AI and ML, have opened new frontiers in software application development. Developers worldwide are increasingly leveraging these innovative digital technologies to build apps that mimic human behavior or support their needs for applications that understand and interpret human behavior. Businesses can leverage these new-age capabilities to engage their customers better, increase customer lifetime value, and build new sources of revenue.
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