Future Impact of Artificial Intelligence in Software Development

Post Date: October 16, 2019   Tags: , ,    Author: texol  

It goes without saying that the impact of Artificial Intelligence in software development is creating a new standard in the software industry. Not only does the AI speed up the software development life-cycle, but it also brings about changes in how enterprises run business and make software intelligent. The role of AI or machine intelligence is beyond compare, particularly in the scenario of increased computational power at reduced costs, and the technology breakthrough. Machine learning is now becoming a reality in every sphere, in software development too.

What Impact does the AI bring into your Software Development?

Artificial intelligence has changed the face of application development. Though the practices that focus to shorten the system development cycle is available, developers sometimes find it difficult to turn ideas into codes. AI removes this obstacle by having expert systems recommend possible changes in code and how to apply them in a software development phase. The extreme impact of Artificial intelligence in software development lies in figuring out how humans perceive and execute the software development process.

Traditional software can’t be completely replaced easily with AI. The areas or components which are critical to the system such as data management, security, and front-end interfaces can only be handled via traditional software. However, the technology developed using the traditional Software development life-cycle method still can take advantage of machine learning methods.

Prototyping Made Simple

Developing a working model of a product or the system needs more time for software developers. With the machine learning algorithms, the prototyping can be made simple without much human intervention. This allows for even the less technical experts to develop solutions using either natural language processing or visual interfaces.

Information Gathering

Information gathering obviously need human intervention. At the same time, AI comes with various tools (Google ML kit and Infosys Nia) that help reduce human involvement to a greater extent. This puts much importance to detect any adequacy before moving to the design phase. To make machines understand the user needs in natural language, an AI technique called natural language processing will be used.

Smart Programming Assistants

Programmers spend most of their time reading the documentation and debugging the code. This puts enormous weight on their heads. Smart programming assistant eases their overheads by giving timely support and guidance with supporting documents, best practices and examples of codes. Kite for python and Codota for Java are the examples of smart assistants.

Analytics and Error Handling

This is another phase in the software development phase. Programming assistants are capable to identify common errors. After the deployment of this technology, machine learning can be used to examine the system logs to proactive errors. We can expect in the future that the software dynamically changes in response to the errors without the need for human help.

Software Testing

Software development is incomplete without software testing. It makes sure the quality of the final product. Whenever the source code needs to be repeatedly changed and the same software tests to be done again, it is time-consuming and costly even. Here the importance of Artificial Intelligence AI comes into play. There are AI tools to automate the testing process and further ensure the error-free software. Appvance IQ is an example of an AI-based testing platform.

Accurate Estimates

Often, Software development companies cannot come to a precise budget and timeline calculation for bigger projects. Precise estimation of projects does need immense expertise, understanding of project context, and acquaintance with the coordination and implementation team. AI can train on grabbing information from previous projects and that includes the user stories, estimates, feature definitions and so. From this information gathering, the system can predict an accurate estimate to the project.

Decision Making

A substantial time of developers is spent discussing about the features to give importance and which to cut. Machine learning solution trained on prior development projects can assess the progress of current projects which help the software developers and testers to maximize impact and minimize risk.

Benefits of AI in Software

You can make a guess how impactful and useful the AI technology has on software development projects. With the understanding of this, Software development companies can now deploy this technology without any hesitation to achieve project goals, to increase test automation, accurate estimates, decision making and to achieve high-quality products. From ensuring data security to decision making to developing error-free codes, AI in software is a bigger gain to software development companies.