Artificial intelligence (AI) is ever-present these days, so naturally, it’s making its way into software development, allowing us to optimise and enhance certain parts of the process.
Today we want to talk about AI in testing automation, explore its potential, look at the current use cases, and see what benefits it brings to software developers.
How is AI used for testing automation today?
If you’ve not looked into the application of AI in software development and testing, you might be surprised how many options are out there already.
- Test execution.
Testing is a critical part of development. It’s also very time-consuming and requires a lot of knowledge and attention to not miss minor inconsistencies or critical bugs. AI can take this load off the dev team’s shoulders and run the tests while everyone is working on new features or taking a much-needed break. - Test planning.
Not only can AI execute the tests, but it’s also extremely useful in the planning phase of testing. It can draw up endless scenarios for testing, and do it much faster than a human being. - Pulling advanced analytics.
The beauty of doing tests automatically with AI is that you can seamlessly generate reports and have the AI go through tons of data to identify trends, co-dependencies, bottlenecks, spot weak areas, and whatever else would help you optimise the process for the future. - Quality assurance.
The machine can make mistakes too, but it’s far less likely to do so than a human employee. This makes AI testing a perfect tool for achieving a consistent quality of testing that you can guarantee to internal and external stakeholders. - User interface testing.
Not only does the AI test the software for bugs, but it can also test how user-friendly and intuitive an interface is. - Test maintenance.
Software testing doesn’t end with the product’s release to market. All updates, changes, and enhancements that occur later must be checked too. And unless the product is going through a major transformation, there’s no need to run extensive tests again. Here, AI can track all changes and run new tests or re-run some previous ones to ensure the latest edition matches all safety and performance requirements.
Key benefits of using artificial intelligence in software testing
AI has a lot to offer in software testing. Here are the main pros that your team will get if you implement the technology in your development process.
Increased testing efficiency
You do more in far less time with automation. There’s probably going to be a bit of downtime at the start when you’ll be writing all scenarios for the AI. However, once the process starts, it will quickly compensate for the time invested earlier.
Higher productivity by the development team
Development is complicated and it is expensive. By automating testing with AI, you’ll free up the hours and days of your valuable employees. Without manual tests taking up their schedules, they will be able to work on other important issues, or finally deal with the tasks that are constantly pushed back by other more urgent things.
Broader scale of tested scenarios
It’s pretty much impossible to match the capabilities of AI in software testing. You’d need to have an army of QA specialists testing the solution 24/7 for weeks, and even then the AI will most likely beat your team’s results.
Continuous learning
Just like your human QA specialist, AI can and will learn. The more it plans and executes software testing, the better it “understands” the job and performs the next time. This means that your ROI in AI testing automation will grow over time.
Potential issues with AI in testing automation
Nobody is perfect, not even AI. Unfortunately, there are potential downsides to automating your software testing that are worth considering too.
- AI can be difficult and expensive to train. But so are human testers, to be fair.
- Poor quality test results are possible if the AI is not well-educated yet, or if it was developed incorrectly from the start.
- AI is prone to bias. Surprising to many, AI is not free from bias because it is created by humans and the data that people feed it. So if the developer who’s working on AI is prone to certain views and stereotypes, the AI they create will likely inherit them.
Bottom line
There’s no denying that AI is changing the world we’re living in. Dystopian future fears aside, it’s a powerful technology that can take a lot of the workload off our shoulders, and help us focus on more creative and complex tasks. In development, AI is useful beyond testing automation. It can help with code writing, risk strategy planning, feature set brainstorming, and more.
It’s not likely to be able to replace us completely in development, at least not in the near future. Still, there is a lot we can enhance and elevate with AI. The Emphasoft team has been integrating this revolutionary technology into many clients’ projects. If you’re looking for advice or would like us to help you automate your development with AI, please feel free to reach out. We’d be more than happy to consult you and share our thoughts and perspectives on your product, development automation, and beyond.
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