Since its inception in the 19th century, Artificial Intelligence is a growing topic of conversation in both science fiction and intellectual debate. To Cut a long story short, AI turns out to be the most disruptive and pervasive technologies of the current digital revolution. Right from automobiles to health care, home automation, aerospace engineering, material science, sports, the technology has been used very creatively, in hitherto unheard of sectors and has the potential to profoundly affect how we interact across the globe. As a result, the tech industry’s interest becomes stronger than ever.
According to the Oxford dictionary “The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages” In a layman’s language, computer systems requiring human intelligence are now able to perform anything and everything; no wonder that many professionals look at AI as a threat. In fact, several jobs are under threat and some will be totally replaced. As absurd and dreamy as that might sound to some, it could very well be true.
AI and deep learning will definitely mean changes in how software is written, said Jim McHugh, vice president and general manager for Nvidia’s DGX-1 supercomputer. According to the market report “By 2018, more than 60% of enterprises will make use of the AI driven technology to automate semi-sophisticated redundant tasks.” Well, that doesn’t mean that computers are going to rise up and steal all the jobs. Now, let’s go a bit closer to understand how Artificial intelligence might affect Software developers across the globe.
Impact of AI on SDLC
Testing is the most obvious areas that will be affected by AI and this has been proved by the rising levels of software complexity and automation. However, achieving better code coverage, identify outliers quickly, find more effective ways to engage in testing are some of the key benefits of including AI into testing. Moreover, by pinpointing production bugs and remedies at regular intervals, you can automate decision making on what to build or test next with great confidence.
Apart from testing, Artificial Intelligence is expected to influence Software Development Life Cycle at the front end starting with ideation. This will not only result in clarity thinking but it will also be capable of suggesting new ideas. The technology comes in the form of a natural language processing (NLP) interface where developers simply need to type in an idea, the one which can be translated into a code which is executable. Besides, devOps is also expected to benefit from AI as it can identify the root cause of a problem and even prevent that same problem from recurring in future.
It’s time for Software Development Teams to Think Differently
Do you know what keeps software developers up at night, other than coding these days? The fear that artificial intelligence systems can replace them, which is true to a great extent. The tables can be turned around, all you need to do is change the way you approach development. Shift the entire process from being rules-based programming to building self-learning capabilities into software and see the magic. Which means developers won’t be able to create an app for a particular outcome, instead the applications developed will need to be able to handle a variety of outcomes.
The major paradigm shift for a software development company would be to stop thinking about programming as a step by step process. And soon they require to allow the system learn and make decisions on how it chooses to move forward which might be difficult to accept. One of interesting examples of how AI can help developers work better together is the use of agile development featuring AI to improve estimates. Artificial Intelligence is well-placed to provide guidance on estimates, especially where there are complex interplays observed between different variables and a lot of data available from previous projects.
With AI, bots, and ML joining the development teams, they would be able to come up with something that’s totally unexpected. Roles and jobs are more likely to shift in ways that may or may not be anticipated. But the overall work flow and team productivity are definitely going to improve and soon it will become hard to stay away from the radars of such disruptive technologies.