| | NOVEMBER 20219systems. As mentioned at the Google conference, we are moving from mobile-first to AI-first world, and this is happening very fast. The interaction between artificial intelligence and mobile apps are quintessentially known as intelligent apps.The DifferenceThese apps use AI, ML and real-time data to make smart decisions and deliver a highly personalized experience to the users. I-apps combine predictive & 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 that call for interactive user experience.MechanismIntelligent 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 & Google AssistantAfter introducing Windows 10, Cortana is a well-known application for all. Previously, the app was only available for Windows phone, but now, it is 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).ConclusionThe most basic function of any intelligent mobile app would be to nail predictive analysis. Intelligent 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.
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