The software testing industry is an enormous facet of our economy. In fact, global application testing services are expected to grow to $55 billion by 2023. This rapid growth is being driven by two factors: digital transformation and the mass migration of applications to the cloud.
But around 90 percent of that budget is currently being spent on manual testing processes, which result in slower product delivery, error-prone tests, and poor quality. That’s where artificial intelligence is changing the game: By using new AI software developed specifically to automate the software testing process, businesses both small and large can save huge amounts of time and money and transform their development infrastructure.
How are these new autonomous testing practices making an impact on the software testing industry?
Low coding, high impact
In today’s digital age, coding is hailed as the equivalent of literacy. It’s becoming an ever-increasing priority for students and professionals alike. Since the Dotcom bubble, software developers have become idolized as the most valuable resources in an organization — with some companies actually more worried about access to software developers than money. Because of this, developer support teams consisting of manual testers, business analysts, and technical writers often become overlooked.
This is all about to change with the use of AI in software testing. Because new AI systems only require the user to have a basic understanding of coding, there is no longer a need to write and test hundreds of lines of code per day. Instead, testers only need to interact with the intelligent system by telling the machine what to do and letting it do the hard work.
Changing the development cycle with smart systems
AI-powered intelligent systems are beginning to take hold across the development lifecycle. A Forrester Research report on AI within software development stated that automated testing and bug detection tools are the biggest factors of interest in AI applications for development processes.
When companies begin applying smart systems to their software testing processes, employees are no longer forced to spend their valuable time on writing code, reworking systems and keeping up with software maintenance. Instead, they can use that time to look for other places to test. By using the context from triggering new builds to know what to maintain, developers can start acting in tandem with the rest of the IT processes.
Bridging the technical gap between teams
As AI bridges the technical gap required in many jobs, more people will be able to add tremendous value to development teams — without needing to have a PhD in computer science. Just like we don’t see modern IT jobs centering around kernel development, the majority of IT jobs future won’t focus on writing code, but rather on managing large software factories.
In the case of autonomous testing, developers, BAs, and product managers alike can be more productive than the best automation engineers in the market today. They can achieve this simply by using AI systems to allow those who are great at understanding quality to fully test software, while the automation engineers can focus their talents on developing more critical applications. Finally, teams can let intelligent systems eliminate a critical bottleneck, without getting lost in the noise.
Using AI to simplify and scale
To avoid getting bogged down by complex systems, companies must turn to new technologies like AI to simplify and scale the jobs done by software development teams today. In fact, we already see the seeds of this change taking place in the adoption of cloud technologies and DevOps initiatives.
With the introduction of AI-powered testing software, the IT and software development industries have no choice but to move away from handcrafted, unmaintainable systems into industrial software development teams. To get there, these new AI systems akin to software factories will lead the way and change the type of work software teams do, allowing machines to do the hard work so that employees can use their talent in more productive spaces. In the process, they will transform the software testing economy.
Interested in learning more? Find out where there’s a bigger problem than A.I.
