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How artificial intelligence and machine learning are revolutionizing software development

Artificial intelligence is the hottest buzzword today, affecting every industry in the world.

AI can be seen as a process of gathering knowledge, acting as human beings and using that learning to adapt to new environments and scenarios.

Artificial intelligence can adapt to all walks of life, it can automate existing processes and can only replace people up to a certain area. AI systems can demonstrate some level of human intelligence behavior such as planning, learning, creativity, manipulation, movement, and many others.

The software development industry is certainly the biggest beneficiary of artificial intelligence technologies, as almost any process can be improvised with the implementation of AI.

Still, it is important to understand that artificial intelligence alone cannot replace humans to perform complex processes and functions, which is why AI is used along with other technologies such as Machine Learning or NLP (Natural Language Processing) to the software development life cycle.

Software Development Companies are always at the forefront of technology, 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 life easier for software developers by transforming the software development lifecycle, resulting in higher quality software.

How AI and Machine Learning are revolutionizing software development

Let’s take a look at different ways AI and ML can transform software development, and for the better.

AI Managed Code Compiler

Software developers use AI-managed code compilers to convert the software code into machine language. We can use Glow or Compiler.ai, which act as a backend for high-level ML frameworks, enabling 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 stage and we can expect some great features and functionalities from them in the future.

AI-based programming assistants

These tools are quite popular among software developers as they can help 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 any programming language.

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

AI-assisted automated software testing

AI can make the software testing process faster, easier and less time consuming. Artificial intelligence improves the accuracy and effectiveness of the software testing process because it cannot make mistakes and lose concentration while working on a large amount of data.

AI-assisted automated tests identify bugs and create reports without human intervention.

Eggplant and Test Sigma are two popular AI-powered software testing tools that help software testers write and run automated tests to reduce bugs and improve software code efficiency.

Software Security

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

Organizations around the world are using AI to capture the data and using machine learning to distinguish deviant behavior from typical behavior. AI systems can be used to detect malware for cybersecurity, perform pattern recognition, and observe malware behavior before it enters the system.

Automated DevOps

AI and machine learning can improve the software deployment process, requiring developers to upgrade codes and applications to newer versions and perform various other software deployment auditing tasks.

The software can be compromised if developers fail to properly deploy and upgrade the applications. AI and ML enable developers to avoid such issues during upgrades and reduce the chance of a failed deployment.

AI helped Machine Learning algorithms examine the implementation process and identify potential bottlenecks and their respective solutions for the developers.

Accurate planning and cost estimation

Planning and cost estimation play an important role in the software development process. AI can be used to propose a software development road map. We can enter the initial status of the company, describe the goal and give a list of possible actions. Based on this model, the AI ​​tool can calculate possible outcomes and challenges, which not only improve decision-making, but also help organizations make the necessary adjustments on the fly.

  • We use a similar model to estimate the cost of a software product. We can enter the necessary information into the tool, after which machine learning algorithms can calculate and determine the possible variants, along with their costs.
  • Accurate planning can influence the software development process as it allows companies to manage their financial assets and create project plans. AI and ML based tools can be used to develop accurate solution development planning.
  • We can take advantage of the following benefits of this AI-assisted approach:
  • Intelligent and faster data analysis.
  • Allows the system to determine key parameters and develop a strategy.
  • Improves the system’s ability to handle incomplete data

A better understanding of user behavior

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

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

AI and ML have been implemented in Online Marketplace portals, where they can improve software functionality, capture user feedback, reduce friction points, prevent cart abandonment and increase conversion rates.

AI-assisted strategic decision-making

AI algorithms help software development organizations to follow the right development methodology to deliver the perfect solution. These algorithms use AI and ML to create key business KPIs, build a suitable framework, and other key indices.

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

Therefore, management is recommended to review the decisions and make necessary changes to the strategy if necessary.


Artificial intelligence combined with machine learning and deep learning and NLP create some unprecedented opportunities to transform the software development process. In layman’s terms, we can say that AI-assisted tools mimic human behavior and perform some routine tasks with the utmost efficiency.

AI and ML-powered tools make software developers and testers more effective and productive by allowing them to build high-quality software solutions. AI and ML not only help companies develop software, but also help them understand customer behavior, test the code, equip the code with adequate security and make strategic decisions. With all of this in mind, technology leaders must turn to AI-powered tools and technologies to transform their software development process.

Author Bio

Gourav Sharma is a digital marketing strategist at Arka software, 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.

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