Artificial intelligence (AI) rapidly turning into one in all the foremost in style topics in each business and science, and a Google’s $400 million acquisition of DeepMind may be a prime example of mainstream AI application, on the other lot leading technical schools, corporations are showing their interest in AI investment. Nevertheless, a research conducted by the “McKinsey & Company” also discovered that the tech giants like “Baidu” and “Google” spend almost about $20 billion to $30 billion on AI, so with 90th of this spent on Research and development preparation, and 100% on AI acquisitions. Nevertheless, as mobile application development evolved, artificial intelligence so has also opened the gates as well as redefined the concept of human-machine interaction. So, today with the vast competition in the market numerous iPhone and Android mobile application development companies fail to meet customer’s expectation regarding loading time, speed, bugs and not able to provide a satisfactory user experience. However, many people also inclined towards mobile devices to get their things done within minutes. Hence, it is clearly shown that the enterprises need to invest in Artificial intelligence mobile app to provide a seamless user experience.
What is Artificial intelligence?
In simplest terms, AI involves machine with the flexibility to repeat intelligence behavior. So, AI prospects are endless, but inside the context of mobile, it is often embedded victimization chatbots or in context-aware sensors. Thus, various enterprises are adopting AI mutually of many tools to have interaction intuitively as well as ultimately to retain their users. According to the research conducted by Gartner, Inc.' intelligent apps are among the highest 10 strategic trends for 2018 and over simply digital assistants can build it simple to finish everyday tasks like prioritizing mails and so on. Gartner also anticipated that two hundred of the world’s largest corporations can also develop intelligent apps in the following year. So, the difference between artificial intelligence, machine learning, and deep learning is in simple terms machine learning is a set of AI which can help to give computers with the flexibility to be told while not express programming to adapt once exposed to new information and deep learning is a branch of machine learning supported by a collection of algorithm, which can help to decide to high-level model ideas or information.
How AI will help to meet the user’s expectations?
Artificial intelligence brings more convenience, features, and functions to any mobile app. So, nowadays mobile apps continue to utilize some form of AI to improve overall user engagement, ease, and personalized experience. Therefore, an app with AI can help to meet customers changing requirement. So, the user of artificial intelligence and machine learning can also allow developers to create highly interactive apps that know how to organize or analyze data which can help to create the possible, engaging experience for the users. Therefore, AI-driven apps have done a lot to make average consumer life easier. For example, VPN apps like Amazon’s Alexa and Apple’s Siri shows that AI is the new way to go when it comes for mobile app development.
AI intensifies user experience and retains engagement
Artificial intelligence is a trusted aid for keeping users engaged based on their behavior and response patterns. So, when this put into action, a mobile app which is AI-infused can help to extract a lot of user information and then it can analyze the data for behavior patterns, which can be valuable for improving the app. So, AI can also document location and transfer the data, to help you for better user experience. Additionally, the user experience is further improved by the ability of AI bots to interact with the user when there is a problem, but the bots seem to be doing it better than standard customer service. Usually, apps don’t fail because of bad ideas, but it fails because they don’t continue to engage users. So, AI is one of the essential parts to monitor the choices as well as trends of the user and feeding that data into algorithms.
Below are the given ways, where Artificial intelligence enabled mobile helps the businesses to create a great user experience for customers:
Expansion of Artificial intelligence in the mobile application has given mobile app users a complete replenishes on the existing user experience. So, with the Artificial intelligence, there are a vast amount of data available’ to talk about the customer spending hours in aisle, interest, purchasing behavior, and so on. Nevertheless, the technology also understands customer behavior in a couple of minutes and can provide in-depth insights into customer preference. Therefore, Starbucks came up with the AI-powered mobile app known as My Starbucks Barista’ where users have to tell what they want, and then the order will be placed. On another end, Taco Bell also came up with a mobile app called TacoBot, so this help to provides personalized menu recommendations by anticipating the interest based on their previous or past purchase. Thus, AI infused apps, or smart apps are now built to ease the task of customer, and when it comes to eCommerce, retailers the use of mobile app development gain customer’s insight based on the user behavioral pattern, so this provides the personalized approach to each customer by giving them shopping recommendations, coupons, discounts and so on. Hence, personalization helps to provide numerous ways of offering to promote the brand to boost its sales to results in app retention, app engagement, and ultimately contribute to increasing the return of interest.
Better predictive reply
A predictive reply is a form of communication between the user and a device where AI technology understands the message and then responds it precisely, so this helps to extracts the information from the existing data sets in order to determine the pattern as well as to predict the outcome. For example, Google Gmail app has come up with the new feature of smart reply by using an artificial intelligence neural network to send appropriate responses to the email messages. So, the feature is integrated by including machine learning to analyze emails and recommends quick, small size messages which you might want to send. Therefore, predicting replies can also help in providing fast replies, to make it easy for the customers as well as brands to resolve the queries in less time. Moreover, chatbots also interact with the users in a natural way, so this helps to create an excellent experience for any user.
Voice based search
The day is not so far when your dinner table would be your search bar and night lamp would be like' how to buy for the best bulbs, and also your car might be finding the YouTube video for how to make the long drive less tiresome. So, the world will be like, you don’t have to waste your energy even for lifting a finger to get the everyday task done, so the thing which you need to do is to turnaround any object and then speak what you are looking. However, a company like Amazon has introduced Alexa to make the task easier just by commenting on the things, so Alexa would do everything. For example, if you can tell Alexa to book your favorite restaurant, then Alexa would do it for you by asking the further additional preference. So, as per the recent survey by “Comscore” shows that by 2020,200 billion searches per month can also be performed by creating the market opportunity voice search of $50+ billion per year, so as the demand increases, then the more useful data will also become available because the better algorithm will also work with speech recognition accuracy. Thus, it is also helping to provide an intense improvement inaccuracy.
Artificial intelligence enabled machine learning mobile apps to refer to the technique involved in dealing with numerous data and then digging out the actionable insights. So, machine learning is one of the best computing processes for providing efficient, cost-effective, reliable solutions to increase the decision-making process from the data-driven affair. However, machine learning AI infused mobile apps also help the doctor to monitor the health of the patient, and at the same time, it also enables the doctors to alert the medications necessary on the particular data. So, the more personal data served to the machine learning algorithm, the more it will help to understand the user’s profile to enable doctors to cure Anomaly on the spot. On another end, Facebook newsfeed also uses AI integrated machine learning algorithm to personalize user’s feed, so if the user frequently like someone post or any particular post then news feed will start to give you similar kind of feed. However, the software uses statistical analysis as well as predictive analytics to recognize the pattern of user data to show similar newsfeed. So, if the user stops to read or like the particular feed, then a new set of data will be generated along with the newsfeed will adjust accordingly.
Below are the given examples for machine learning artificial intelligence mobile app:
· Product recommendation
· Self-driving car of Google
· Knowing what your customer is going to say on social media
· Fraud detection
Boost the content quality
Artificial intelligence ruling the market by collecting a vast amount of data across numerous platforms like data management, data lakes, data warehouses, and other repositories of structured and unstructured data. So, data fetching can help in designing content or help for enhancing business intelligence to provide preciseness. Moreover, it also helps the search engine to fetch the result which is more appropriate because the search engine is becoming smarter, so there is no doubt in expecting that these strategies are brilliant for better ranking in the long term. However, elements like unique style content, tone of writing, USP are crucial for every business and for that AI helps to create ads, blogs, article, summaries and some promotional material using the data being fed on it, so as long the data is good, then AI can also help to create campaigns quickly and easily than human.
So, for wrapping up,’ the increasing use of AI in mobile application development services revamped the business growth as well as it also helped for user engagement. Hence, Siri, Cortana, Microsoft are some of the trending tech giants, which come with the AI-powered mobile app to change the way how a user communicates and have reached the new level. However, it also has the potential to intensify the reach as well as app retention, so the growth of AI enabling multiple possibilities in numerous enterprises to dominate the app market.