Role of Artificial Intelligence in Software Development

Heading towards automation

Artificial Intelligence has brought groundbreaking transformation in software development, cranking up the productivity of developers and engineers by automation of multiple tasks. From face detection and recognition to ride hailing apps such as Careem, InDrive and Uber, AI unfailingly surprises us wherever we go. At every step, AI has been supporting the software professionals by way of honing the software processes and incorporating machine learning. With an increase in mechanization, AI seems to be promising while also unburdening many humanly tasks. Let’s have a look at how AI has eased the software development lifecycle:

1.     Decision making is now faster and better 

AI has swayed the strategic decision making process by limiting human interference through automation. Previously, the management wasted time on discussing which will be the most feasible product, services or feature in which they should invest, AI had made this simple. If the company's AI is adjusted to analyze the pros and cons of a software, it can quickly give performance reviews on updated and new software while also mitigating the risks. Decision making now depends on analytics which will be beneficial in reducing cost and minimizing human errors. Machine learning makes use of the data by gathering and assessing it and on that basis the computer interprets and makes informed decisions. The data can assist in making quick witted and smarter decisions.

2.     Diverging the role of developers

AI is now shifting and morphing the software developers’ role. By assigning specific duties to AI machines, they can polish their other skills and focus on other sets of tasks while simultaneously corresponding with Al. This not only saves their time but also gives them an opportunity to explore new avenues and deal with complex issues. Programmers can work side by side with AI, since it cannot outperform manpower. Coding can be done by AI but software development is challenging and requires human intelligence to decipher, control and give directions. 

3.     Estimates can be precise too

There are tasks in which machines cannot transcend the human brain and vice versa. Same goes for making estimations and predictions. Software developers cannot always make efficacious or close estimations on costs and project timelines. Through Al, you can have a precise estimation of resources, budget needed, how much time and effort will be required to complete a specific task. Based on that, programmers and developers can accept a project. By giving accurate information to your clients and informing them on project progress, there are chances that clients might hire you for future tasks.

4.     Faster Development and less errors 

Machine learning can reduce the time span of many processes by performing automated tasks. For example, there is no need for quality assurance experts to waste time on strenuous software testing. Instead, AI can do this without wastage or any errors. Computers, backed by AI, can perform complex repetitive processes quickly and efficiently. If errors are detected in the software, it can diagnose and correct it on the spot without manual intervention.

5.     Performance management strategy 

With machine learning algorithms, companies can get instant feedback from users. AI enabled software gives developers a clear picture of what areas need further refinement, enhancing customer experience.

Artificial Intelligence is becoming a necessity in this fast paced software industry, where programmers have to align themselves to the latest trends, so investing in AI is crucial.