How Artificial Intelligence and Machine Learning are Revolutionizing Software Development

Gourav Sharma
Published 10/30/2021
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Computer with a printer beside itArtificial intelligence is the biggest buzzword these days and it is affecting every industry in the world.

AI could be considered as a process of collecting knowledge, acting as a Human being, and using that learning to adapt to new environments and scenarios.

Artificial Intelligence could adapt to all walks of human life, it can automate the existing processes and can replace humans up to a certain area only. AI systems can prove a certain level of human intelligence behavior such as planning, learning, creativity, manipulation, motion, and many others.

The software development industry is certainly the biggest beneficiary of Artificial Intelligence technologies, as almost every process could be improvised with the implementation of AI.

Yet, it is important to understand that Artificial Intelligence alone can’t replace humans to perform complex processes and functions, that is the reason why AI is used along with other technologies like Machine Learning or NLP (Natural Language Processing) to automate the steps of the software development lifecycle.

Software development companies are always ahead on the technology front, as it receives innovative and complex solutions. Software developers use AI tools to plan and schedule projects, automate testing, code compilation, decision making, and many other tasks.



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Artificial Intelligence makes the life of software developers easier by transforming the Software Development Life Cycle, which results in higher quality software.

How AI and Machine Learning are revolutionizing the Software Development

Let’s take a close look at several ways how AI and ML can transform software development, and that too for the better.


AI-managed Code Compiler

Software developers use AI-managed code compilers to convert the software code to machine language. We can use Glow or, which act as a backend for high-level ML frameworks, that enable code generation and optimization of neural network graphs.

These AI tools use Machine learning to improve the speed and quality of code compilation. These AI-managed compilers are still in the development phase and in the future, we can expect some fantastic features and functionalities from them.


AI-Based Programming Assistants

These tools are quite popular among software developers, as they can assist a developer with code compilation, code debugging, and code-driven testing. Kite and Codota are examples of AI-based programming assistants, they allow developers to write code in almost every programming language.

These programming assistants can use the libraries and complete the code lines and fix the syntax. These tools are developed and trained on learning models, that use Machine Learning to write codes with less typing while increasing productivity.


AI-Aided Automated Software Testing

AI can make the software testing process faster, easier, and less time-consuming. Artificial Intelligence enhances the accuracy and effectiveness of the software testing process, as it can’t make mistakes and don’t lose concentration while working on a large amount of data.

AI-aided automated testing identifies bugs and creates reports without any human intervention.

Eggplant and Test Sigma are two popular AI-aided software testing tools, that help software testers to write and execute automated tests to mitigate bugs and improve the efficiency of software code.


Software Security

Security is the most critical feature for any system, as software collects sensitive data and then applies business logic to process them.

Organizations across the world are using AI to capture the data and use Machine Learning to distinguish anomalous behavior from typical behavior. AI systems can be used to detect malware for cybersecurity, execute pattern recognition, and observe behaviors of malware before it enters the system.


Automated DevOps

AI and Machine learning can improve the software deployment process, where developers must upgrade codes and applications to newer versions and carry out several other software deployment control tasks.

The software could be in jeopardy if developers are unable to deploy and upgrade the applications correctly. AI and ML enable developers to prevent such issues during upgrades and reduce the likelihood of deployment failure.

AI aided Machine Learning algorithms to examine the deployment process and identify potential bottlenecks and their respective solutions to the developers.


Precise Planning and Cost Estimation

Planning and Cost estimation plays an important role in the Software development process. AI can be utilized to propose a software development roadmap. We can input the initial state of the company, describe the goal, and provide a list of potential actions. Based on this model, the AI tool can calculate possible outcomes and challenges, which not only improve the decision-making but also help organizations to make necessary adjustments on the fly.

  • We use a similar model to estimate the cost of a software product. We can enter the required information in the tool, then Machine learning algorithms can calculate and determine the possible variants along with their cost.
  • Precise planning can influence the software development process, as it enables companies to manage their financial assets and make project plans. AI and ML-based tools can use to develop precise planning for solution development.
  • We can avail the following advantages of this AI-aided approach:
  • Intelligent and faster data analysis.
  • Offers an ability to the system to determine important parameters and develop a strategy.
  • Improves the ability of the system to handle incomplete data


A better understanding of User behavior

Machine learning algorithms can help us understand the user behavior and then deliver variable content by adjusting screen size, font size, buttons, and several other on-page elements.

Such personalized and dynamic responses can improve the user experience and it also allows developers to make appropriate changes in the code by observing the real-time user interaction data.

AI and ML are implemented in Online Marketplace portals, where they can improve the software functionality, capture the user feedback, reduce the friction points, prevent abandoned carts, and increase the conversion rates.


AI-assisted Strategic Decision Making

AI algorithms assist software development organizations to follow the correct development methodology to deliver the perfect solution. These algorithms use AI and ML to create major KPIs for business, set up a suitable framework, and other important indexes.

AI and ML-aided software can analyze and develop the best decision-making methods, which can help developers to make effective decisions. Even though AO and ML can transform the strategic decision-making process, but these algorithms are not perfect and may not adapt to dynamic programming environments.

Hence it is recommended for management to review the decisions and make appropriate changes in the strategy if required.



Artificial Intelligence coupled with Machine Learning and Deep Learning, and NLP create some unprecedented capabilities to transform the software development process. In layman language, we can say that AI-aided tools mimic human behavior and fulfill some routine tasks with utmost efficiency.

AI and ML-powered tools are making software developers and testers more effective and productive, as it allows them to build high-quality software solutions. AI and ML not only help companies to develop software, but also assist them to understand customer behavior, test the code, equipping the code with adequate security, and make strategic decisions. Keeping all this in mind, technology leaders must opt for AI-powered tools and technologies to transform their software development process.


Author Bio

Gourav Sharma is a Digital Marketing Strategist at Arka Softwares, a leading mobile app development company. He has 4 years of experience in the Information Technology industry. He spends his time reading about new trends in Digital Marketing and the latest app development technologies.