Intelligent Apps - The Future of Mobile Apps
CEOInsights Team, 0
Today, smartphones have transformed the entire process of each and every realm, and what makes smartphones irresistible is the ‘full of potential’ apps that we download in these devices. These apps are responsible for unlocking the full potential of a smartphone, which further helps us to make our lives easier. Nowadays, technological innovation in cloud infrastructure and machine learning laid as a foundation for tomorrow’s intelligent apps (I-apps). I apps are the next generation of apps that make our everyday tasks and experiences remarkably well. Thanks to these apps, our smart phones automates tasks recognizing our speech, help us make confident decisions, and enable us to understand unknown languages through translation.
About Intelligent Apps
Intelligent things are poised to be one of the important trends that have the potential for ‘disruption’ and large-scale impact across industries. According to Gartner, the future will see the utilization of AI by almost all apps and services, making these apps discreet yet useful and intelligent mediators between systems and humans. AI is paving the way for almost all the industry. Mobile apps aren’t too far behind in this context. Mobile apps are now witnessing the much-needed infiltration from the artificial intelligence segment. The possibilities are now endless. AI will be incorporated into various systems and apps in some way and is poised to become the key enabler across a variety of services and software systems. As mentioned at the Google conference, very fast, we are moving from mobile first to AI first world. The interaction between artificial intelligence and mobile apps are quintessentially known as intelligent apps.
The Difference
These apps use AI, ML and realtime data to make smart decisions and deliver a highly personalized experience to the users. I apps combine predictive and prescriptive analytics, customer data, product insights, and
operational vision with contemporary user focused design and application development tools to create a highly impactful experience for users. These apps offer a range of value added services and response mechanisms thatcall for interactive user experience.
Mechanism
Intelligent apps extensively use machine learning to define end user experience.In fact, machine learning and data analytics are the core components of intelligent apps. Intelligent apps have AI-powered algorithms which remove irrelevant information and focus on relevant information to make decisions. After understanding the users’ needs, these apps deliver relevant and contextual information and notify the users on the potential problems before they arise. These apps facilitate automatic execution of tasks without specifically waiting for user commands. By applying a very high degree of predictive analytics, these apps predict user behaviour and make the information available in a very easy manner.
Example of I Apps
Cortana, Alexa, Siri, and Google Assistant After introducing Windows 10, Cortana is a well-known application for all. Previously, the app was only available for Windows phone but now available on Android devices too. This application helps you to manage tasks which would need otherwise to do. For instance, one just needs to schedule a meet and rest work will be handled by Cortana. Similarly, Amazon, Apple, and Google’s digital voice assistants are great examples of intelligent apps that combine natural language generation, processing and machine learning. These digital voice assistants have made our lives super easy and convenient as they give updates about weather, traffic, adjust a smart LED, coordinate meetings, and make your moments lighter by telling jokes and playing music. These virtual assistants converse sounding like a human thanks to Natural Language Processing (NLP) and Natural Language Generation (NLG).
Conclusion
The most basic function of any intelligent mobile app would be to nail predictive analysis. Intelli gent apps would be here to think before your user thinks. Based on previous interactions and data collected the user cheat sheet is ready. In the coming future, while companies will continue to use their legacy systems, they will increasingly find ways to leverage I-apps to enhance their business processes. For instance - Simple applications such as emails may not completely go away, but workplaces might create I-apps to add the ability to alert an employee about emails that require instant action or response. Undoubtedly, I-apps are paving the way for speedier business decision making, improve the efficiency of the workforce, obtaining better business results and ensure long term gains; all this needs to be utilized in the right manner. The ultimate objective of I-apps at the workplace will be to work in harmony with existing systems used at the workplace and deliver highly personalized and targeted information that an employee may need to enhance the quality and increase the output of their job. Business organizations which are diving in I-apps now will surely have a competitive edge in the future.
Intelligent Things Are Poised To Be One Of The Important Trends That Have The Potential For‘Disruption’And Large-Scale Impact Across Industries
Mechanism
Intelligent apps extensively use machine learning to define end user experience.In fact, machine learning and data analytics are the core components of intelligent apps. Intelligent apps have AI-powered algorithms which remove irrelevant information and focus on relevant information to make decisions. After understanding the users’ needs, these apps deliver relevant and contextual information and notify the users on the potential problems before they arise. These apps facilitate automatic execution of tasks without specifically waiting for user commands. By applying a very high degree of predictive analytics, these apps predict user behaviour and make the information available in a very easy manner.
Example of I Apps
Cortana, Alexa, Siri, and Google Assistant After introducing Windows 10, Cortana is a well-known application for all. Previously, the app was only available for Windows phone but now available on Android devices too. This application helps you to manage tasks which would need otherwise to do. For instance, one just needs to schedule a meet and rest work will be handled by Cortana. Similarly, Amazon, Apple, and Google’s digital voice assistants are great examples of intelligent apps that combine natural language generation, processing and machine learning. These digital voice assistants have made our lives super easy and convenient as they give updates about weather, traffic, adjust a smart LED, coordinate meetings, and make your moments lighter by telling jokes and playing music. These virtual assistants converse sounding like a human thanks to Natural Language Processing (NLP) and Natural Language Generation (NLG).
Conclusion
The most basic function of any intelligent mobile app would be to nail predictive analysis. Intelli gent apps would be here to think before your user thinks. Based on previous interactions and data collected the user cheat sheet is ready. In the coming future, while companies will continue to use their legacy systems, they will increasingly find ways to leverage I-apps to enhance their business processes. For instance - Simple applications such as emails may not completely go away, but workplaces might create I-apps to add the ability to alert an employee about emails that require instant action or response. Undoubtedly, I-apps are paving the way for speedier business decision making, improve the efficiency of the workforce, obtaining better business results and ensure long term gains; all this needs to be utilized in the right manner. The ultimate objective of I-apps at the workplace will be to work in harmony with existing systems used at the workplace and deliver highly personalized and targeted information that an employee may need to enhance the quality and increase the output of their job. Business organizations which are diving in I-apps now will surely have a competitive edge in the future.