It's Time to Take AI-Driven Software Development Seriously

Considering how complex software applications have become today, requiring deep integration with myriad APIs, legacy systems, and other apps, developers end up spending a massive amount of time in software development. And while they are at it, there are several challenges they encounter, while trying to dodge a plethora of issues all along the way. Enter AI, and software development is a breeze. AI helps in automating a lot of the manual, error-prone, time-consuming software development tasks; developers only have to input relevant data into AI algorithms and improve the quality and accuracy of development. With 80% of enterprises investing in Artificial Intelligence (AI) in one way or another, it’s time to take AI-driven software development seriously.

Here are 6 reasons how AI can accelerate the software development process:

1.    Precise estimates: Software development projects are known to overshoot timelines and exceed the allotted budget; estimating the time, effort, and resources needed for any software project development is hard, if not impossible. Reaching a reliable estimate requires software developers to understand the context, along with the required technology and the capabilities of resources. An AI system can analyze a huge amount of data collected over time from past projects such as features, bugs, development effort, resource capabilities and number, time spent in coding, testing, maintenance, user reviews and more – and use correlations and statistics to arrive at more precise and accurate estimates of effort and timeline.

2.    Rapid prototyping. Turning a business idea into a software product is typically a long and cumbersome endeavor. Just as getting it to a prototype level is. AI can enable software development teams to speed up prototyping; by using pre-defined natural language or visual interfaces, AI can help technical domain experts cut down on the time and effort spent in coding to quickly build prototypes, and convert them into quality products. Developers can focus less on using coded rules to prototype applications and instead configure and train algorithms that can learn from experience.

3.    Quicker decision-making: Given the fact that every business today is investing in software development, the need for fast and accurate decision-making is apparent. Since AI systems can automatically identify features that are important, and pinpoint aspects that carry a certain amount of business risk, developers and testers can prioritize their decisions based on the identified risk and make sure the software product meets the quality level and the intended requirement. By feeding the right data into AI algorithms, software development teams can automate a lot of the tasks, reduce the likelihood of mistakes and human error, and limit the time and money wasted in testing.

4.    Quality development: To err is human. Even the most meticulous developer is sure to make mistakes while writing unending lines of code or while carrying out monotonous manual testing. This is where AI can help; not only can it automate a lot of the development tasks, it can also look into all aspects of software development, identify bugs and issues, and determine if the software is behaving as expected. Developers can get freed from repetitive coding and manual testing and can drive more focus towards gathering relevant information, feeding it into AI systems, and training them to improve accuracy. Not just that, AI can also assess the actual performance of existing features and help business leaders identify efforts that would maximize revenue and minimize risk.

5.    Reduced development costs: For organizations seeking to be more cost-effective, the business case for AI is compelling. Since AI systems are designed to automate simple activities involving coding, data processing, and testing, they drastically reduce the cost (and time) of human effort while substantially improving accuracy; cutting down on development time directly translates into cost savings. What’s more, with software tests having to be modified every time the source code is modified, AI can carry out automated tests as frequently as required, at no additional cost.

6.    Improved time-to-market: With each passing day, software systems are getting more and more complex. A lot of them today have multiple dependencies and require an umpteen number of features and interfaces to be included. With AI, a lot of the software development tasks can be automated: from prototyping to coding, integration to testing, and even maintenance; AI can automate the coding process, and perform the same tests accurately every time they are executed. The end results? Reduced number of discrepancies and bugs, faster development of quality software, and hence, faster time-to-market.  

Transform the software development process

As the intricacy of software products increases, the era of manual coding and testing is over. The era of automation has commenced, with AI as the front-runner. No matter what area of software development you choose to apply AI in, there is massive potential for it to change the way you develop software. So, stop manually developing code and get caught up in the melee of issues and challenges; instead, use AI systems to automate many (if not all) of your development processes, and change the way you develop software. AI can help in accurate and precise estimation, rapid prototyping, accelerating the decision-making process, developing quality software, reducing software development costs, and improving time-to-market. All it takes is to embrace the many new opportunities AI presents, and transform the software development process.