Role of AI in Software Development

In the 21st Century, we were introduced to the concept of automation. Data and machine intelligence are powering this automation. Data simply means a collection of values. In 2022, the per day Data generation stats stand at a staggering 2.5 quintillion bytes, the unit conversion of which to Gigabytes becomes a head-spinning task. Now, you may wonder why a collection of odd values is important in this era where people label Data as the new oil. Here comes into the picture the concept of data science.

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What is AI?

The capability of an artificial machine to think and act like a human can be called Artificial Intelligence. Artificial intelligence is a subset of Data Science responsible for giving life to a machine. The scope of AI is unrestricted, and even the sky’s not the limit as we have AI-powered Satellites launched by SpaceX in space. The use of AI is increasing and advancing in every sector and every field of industry. The algorithm-based machine learning, which is further a subset of Artificial intelligence, is the basis for predictive analysis of data by data scientists. Machines learn through various methods and apply their learnings while deciding or performing a task.

Role of AI in Software Development

Well-established SaaS companies like Netflix, Spotify, Amazon Prime, Youtube, etc., use AI extensively on their platform to cater the customer needs and provide satisfactory service to their users. There has been a growing shift toward AI in Software development, and AI is definitely the future of Software Development.

Increased User experience

Every software must provide a platform for a user to communicate his queries and get a solution. A platform isn’t all but rather an AI-powered platform(AI Chatbots) that replies to every query instantly and gives a top-notch quality experience to users. Almost every customer service website, like IRCTC, BookMyShow, MakeMyTrip, etc., is powered by AI chatbots to help customers. AI-backed Alexa and other intelligent voice assistants have also been helping users with a wide range of activities at the tip of their voices.

Increased speed of development

Machine Learning and deep learning techniques can help DevOp reduce several software testing processes. The quality assurance analysts would no longer be needed to manually test the software as AI would test your software automatically at every stage. Fintech companies are adopting AI-powered trading bots to automate the trades of their books.

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Enhanced Security and Privacy

The stronger deep learning models can classify and identify almost everything in a frame. Hence, AI can enhance security by giving access to only identified and verified individuals while maintaining privacy at the user level by giving different access to different users as defined by the admin. Banking applications exclusively use AI to keep secure the data of their customers.

Recommender system

If your product is a video streaming service or a podcast/music streaming service, then powering the software with a recommender system would boost user experience and user stay-time on your application. The recommender system works by understanding the user’s interests and predicting their next best option. Companies like Netflix and Facebook extensively curate users’ content with AI’s help.

Error elimination

The AI can help diagnose and treat an error without human intervention, which also reduces maintenance costs. AI can use reinforcement learning to deal with errors with the concept of reward and punishment. The data is then retrained to avoid the same errors in the future. This way, it ensures that an error dealt with is an error eliminated forever.

Decision Making and Time estimation

The ability of AI includes the ability to make decisions. Under defined constraints and criteria, the machine can make the most suitable and accurate decision. Different regression models can help predict the estimated time frame and cost estimation for the current project when trained with past project timelines and cost estimations. The supervised and unsupervised learning algorithms can significantly help a developer with advanced services.

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