Can you envision a world without mobile apps in our daily lives?
Does your business run without an app?
Apps have become an essential part of our lives. As from waking us up in the morning to tracking our daily workouts and connecting with friends and family worldwide, they play a major role.
But what makes these apps smarter, more intuitive, and user-centric?
The answer is “ARTIFICIAL INTELLIGENCE in Apps.”
According to Statista, the value of the AI market is nearly $100 billion and is expected to grow twentyfold by 2030, up to nearly $2 trillion
Artificial intelligence app development uses a machine’s capacity to understand and respond, thereby providing the best user experience. The main objective of artificial intelligence in mobile applications is to solve day-to-day problems and make users’ lives easier and more comfortable.
In this blog, we will discuss the benefits of using AI in app development, different AI technologies, and various use cases.
So, let’s dive in and explore the impact of AI on app development.
Why Develop AI-Integrated Apps in Business?
Integrating Artificial Intelligence in mobile app development offer multifaceted benefits for businesses. It enhances user engagement by delivering personalized experiences, boosts operational efficiency through automation, and provides predictive analytics for data-driven decisions.
AI improves security, data protection, and offers valuable insights that improve app enhancements. This dynamic technology not only makes apps smarter but also competitive.
Let’s understand the benefits of using AI in mobile applications and how it can help businesses:
Enhanced User Engagement
AI-based applications use algorithms to analyze user behavior and preferences to provide customized recommendations and content. Through AI, user interactions with apps become more personalized as the algorithms can perform sentiment analysis and define emotions. Moreover, it will generate more opportunities for businesses to improve products and services.
Efficient Automation
With AI-based features, various processes can be streamlined within mobile applications. Tasks like customer support, content curation, and data entry can be automated to reduce manual and mundane work. By automating repetitive functions, the app for businesses can improve operational efficiency and redirect human efforts towards value-added services.
Predictive Analytics
AI-powered predictive analytics helps apps to forecast user needs and future trends by analyzing historical data. It empowers AI in apps to identify potential outcomes by suggesting personalized content, products, or services, increasing user engagement. It also aids in risk assessment, fraud detection, and resource allocation.
Augmented Security
AI systems continuously monitor network traffic, which makes it easy for businesses to identify threats and anomalies in real-time. It is efficient enough to detect attacks and easily adapts to defense techniques to protect mobile apps from probable cyber threats. In artificial intelligence app, AI-driven authentication methods, biometrics, and behavioral analysis add layers of security.
Improved User Support
Chatbots and virtual assistants driven by AI offer round-the-clock support to efficiently address the users’ queries. They can provide instant answers, guide users through processes, and execute tasks within applications. AI-driven user support offers convenience, accessibility, and responsiveness to elevate user experience and loyalty in the competitive artificial intelligence apps market.
Data-Driven Insights
AI processes vast amounts of data, hidden patterns, and trends to empower mobile app developers and businesses to form strategies for better user experiences. From personalized product or service recommendations to optimizing resource allocation, AI has the potential for growth and innovation.
Types of Technologies of Artificial Intelligence in Apps
The fusion of Artificial Intelligence in mobile apps is a pivotal trend as it enhances functionality and offers a unique user experience. While AI development software facilitates this easy incorporation into the app development process, it makes apps more user-friendly, efficient, and engaging.
Let us walk you through different AI technologies that enhance your app development:
Machine Learning (ML)
It is a type of AI technology that allows mobile apps to learn from data and improve without explicit programming. This is made possible by feeding the app with data and letting it recognize patterns, make predictions, and adapt to user behaviors.
How Can Apps Use Machine Learning?
Natural Language Processing (NLP)
Natural language processing technology understands the interaction between machines and human language. It assists apps to understand, interpret, and then respond to textual or voice messages the way the user feels natural. NLP powers language translation apps and chatbots like Siri or Alexa, Chatbots, and virtual assistants.
How Can Apps Use NLP?
Computer Vision
Computer Vision is a technology of artificial intelligence in apps that allows devices to interpret visual content from videos and images. It replicates human visual perception by recognizing texts, objects, and even emotions within visual data. This capability of AI in mobile apps can be used in facial recognition for security, augmented reality for interactive experiences, and object detection for various purposes.
How Can Apps Use Computer Vision?
Speech Recognition
This technology enables devices to convert spoken language into text or commands. It allows users to interact with apps through voice input for convenience, which can also be done with virtual assistants like Siri or Alexa. Speech recognition is used in applications providing transcription services, accessibility features for users with disabilities, and voice-controlled interfaces.
How Can Apps Use Speech Recognition?
Natural Language Generation (NLG)
NLG is an AI technology that allows applications to produce human-like text or speech based on structured data. It empowers apps to generate reports, product descriptions, summaries, and even personalized messages. This technology is used for content creation and customer interactions by adding a personal touch to user experiences.
How Can Apps Use Natural Language Generation?
Case Studies: Successful AI Integration in Popular Apps
NETFLIX
Description:
Netflix is one of the most popular streaming apps, with a vast library of award-winning movies, TV shows, documentaries, anime, and more. It can be streamed from an app on devices like mobile phones, tablets, laptops, TVs, gaming consoles, and setup boxes with an internet connection.
Usage of AI in Netflix:
Description:
It is a free social media platform for users to share their photos and videos with followers online. Instagram is an app that has become popular to interact with celebrities, brands, and friends. Its user-friendly interface and creative features like stories, reels, and filters make it a place for visual storytelling and personal expression.
Usage of AI in Instagram:
UBER
Description:
Uber is a global ride-sharing and transportation platform that connects passengers with drivers through a mobile app. Users can request rides, track driver’s arrival, and make cashless payments for convenient transportation. Uber has revolutionized the way people travel by offering reliable and accessible transportation services.
Usage of AI in Uber:
See Also: How To Build An App Like Uber?
How Much Does it Cost to Develop AI Mobile Apps?
Cost to build an app can vary depending on several factors, like design requirements, the complexity of features, development time, and the location and expertise of the development team.
An MVP- a basic AI-based application with limited features may cost anywhere between $18K to $20K. At the same time, a more advanced version with complex functionalities and integrations can range from from $75K to $150K or even more. However, for the already existing apps, an AI integration can go from $25/hr to $30/hr.
It is important to consider ongoing maintenance, updates, and security expenses. Working with a skilled development team and conducting a thorough cost analysis will help you determine an accurate budget for AI in mobile app development.
How Can Excellent Webworld Help You Get Started with AI in Your Mobile App?
It may seem difficult to integrate Artificial Intelligence into your mobile application, but the right partner, like Excellent Webworld, can make it an exciting and rewarding venture. We specialize in demystifying the complexities of AI and provides you with a tailored solution to make your app AI-ready.
Our efficient team understands that one size does not fit all in the AI world. They approach each project cautiously with a tailor-made strategy. By collaborating closely with your business, we understand your exact requirements and seamlessly integrate AI into your app’s functionality.
With us, your app isn’t just technologically equipped for the future but is positioned for growth, efficiency, and competitiveness.
Trust Excellent Webworld to be your partner, and contact us NOW!
FAQs
AI is used in apps to provide personalized experiences, recommendations, and virtual assistance. It empowers apps with predictive analytics and efficient functionalities to enhance user interactions and convenience.
The first step to incorporating AI in application development is to identify use cases and gather relevant information. You can then select appropriate AI technologies, implement AI algorithms, test rigorously, and update continuously for better performance.
Artificial intelligence can transform the app development process by automating tasks, enhancing user experiences with personalized features, embedding predictive analytics, and streamlining processes. This can save time and improve the app quality.
AI is elevating mobile app technology through personalization, automation, predictive insights, and image/voice recognition. This creates smarter, user-centric apps that perform better and prioritize security.
Excellent Webworld has used various fields of AI in mobile application development, like natural language processing (NLP), machine learning (ML), computer vision, and speech recognition to enhance functionality and overall user experience.
Looking for Product Engineering Services?
