Artificial intelligence (AI) might be a headline-grabbing feature for technology products. But what are the real-world benefits for software testers and development teams that invest in AI-powered test platforms?
AI can help overcome test automation bottlenecks
Despite test automation being widely-recognized as a crucial tool for achieving modern QA and testing objectives, its overall use remains low. But artificial intelligence, like Bitbar’s AI Testbot, can overcome bottlenecks and unleash the power of test automation for DevOps environments.
99% of software companies use DevOps for some part of their business – and test automation plays a crucial role in DevOps environments and their CI/CD pipelines.
Top-reported benefits of test automation include:
- Improved test coverage
- Better control and transparency of test activities
- Better reuse of test cases
- Reduction of test cycle time
- Better detection of defects
- Reduction of test costs
Three-quarters of software companies want to shift to daily, hourly, or weekly build deployment, yet research suggests that test automation is used in less than a quarter of test cases (24%) – which makes it the single biggest obstacle to achieving these levels of responsiveness.
Unfortunately, orchestrating test automation across CI/CD pipelines is increasingly challenging. Nearly two-thirds of senior decision-makers in corporate IT functions report that ‘releases are getting very complex, often involving multiple applications with dependencies and different technologies with potentially conflicting resources’.
But artificial intelligence and machine learning technologies can enable ‘smart’ test orchestration and identify tests that will be needed for each cycle of software development. That’s why more than a quarter of senior decision-makers think that AI-driven test execution is an important orchestration ability.
AI can identify bugs before they become expensive
Bugs become more expensive to fix as the software development process evolves. But artificial intelligence offers instant feedback – which can help identify bugs early in the process and deliver significant cost savings.
IBM’s Systems Sciences Institute reported that the cost to fix an error found after product release was four to five times more expensive than one uncovered during design – and up to 100 times more than a bug identified in the maintenance phase.
How expensive can bugs become if they’re detected late?
- $100 – Gathering Requirements phase
- $1,500 – QA testing phase
- $10,000 – Production
Games developer Ubisoft has built an AI tool that can alert programmers to potential bugs while they type code. Commit Assistant was trained with a database of Ubisoft code and bug fixes that spans a decade. It can identify patterns that suggest a mistake is being created and alert the developer so they can take action.
Bug fixes can absorb 70% of a Ubisoft’s development budget for a game – so AI stands to offer significant financial benefits for their business.
AI test automation can reduce manual test time
Fears of artificial intelligence replacing human software testers are likely unfounded. AI is expected to perform repetitive tasks and free humans to use their creativity and critical thinking skills across a range of industries – including software testing.
Business executives see huge potential for AI to reduce repetitive tasks and free humans to focus on ‘big thinking’. But what does this mean for software testing?
Artificial intelligence can script 100 tests in 1/100th of the time that a single person could. AI can do the ‘heavy lifting’ and perform repetitive tasks like implementing, executing, and analyzing tests. Software testers will increasingly work on high-level functions like monitoring tests, making recommendations, and offering feedback to the business.
AI is already the future
We’re at the start of a fourth industrial revolution – according to Professor Klaus Schwab, Founder and Executive Chairman of the World Economic Forum – in which technology will transform the way that humans live, work, and interact.
‘The individuals who will succeed in the economy of the future will be those who can complement the work done by mechanical or algorithmic technologies, and ‘work with the machines.’
– World Economic Forum
Quality assurance (QA) and testing remain a major cost for software companies (it captured more than a quarter (26%) of IT budgets last year) – so there is a huge incentive to invest in test automation platforms that are powered by artificial intelligence.
After all, the evidence strongly suggests that AI is the missing link that will allow more software companies to embrace test automation and fully leverage agile and DevOps to drive the daily and even hourly release schedules that will become the benchmark for any market-leading software company.