Why Human Software Testers Are Here to Stay

While artificial intelligence has made significant strides in automating many aspects of software testing, a recent survey by Leapwork found that a resounding majority of organizations still believe that human expertise is essential for ensuring the quality and reliability of their software.

A new Leapwork report, AI and Software Quality: Trends and Executive Insights, revealed that 74% of companies think software testing will continue to need human validation.

Despite the progress of AI-augmented testing tools, most C-Suite execs (68%) and technical teams (80%) agree that humans in the loop in software testing are essential.

Leapwork surveyed 401 C-Suite executives and technical professionals to know how companies balance out AI-augmented testing tools against quality.

Techopedia spoke to Leapwork and other experts to understand how testing is evolving and why teams want humans in the loop. If you are looking to become a software tester in 2024, you still have a career path ahead of you.

Table of Contents Table of Contents

1. Key Takeaways
2. Where Does AI Succeed in Testing?
3. Why Humans Are Unlikely to Disappear from Testing Processes in the Future
4. 'Don´t Let AI Run Loose In Your SDLC,' HackerOne Expert Says
5. The Bottom Line
6. FAQs
7. References

Show Full Guide

Table of Contents

1. Key Takeaways
2. Where Does AI Succeed in Testing?
3. Why Humans Are Unlikely to Disappear from Testing Processes in the Future
Show Full Guide
4. 'Don´t Let AI Run Loose In Your SDLC,' HackerOne Expert Says
5. The Bottom Line
6. FAQs
7. References

Where Does AI Succeed in Testing?

First up, where do AI and automated testing go together?

Robert Salesas, Chief Technology Officer of Leapwork, which is an AI testing platform, said: “Traditional tools are pretty good at automating predefined tests, but the advantage of AI-augmented testing is generating entire test cases and scenarios from nothing but a few prompts that include requirements or user stories.

“Companies have tangled spider webs of interrelated applications, whether they’re packaged or self-grown software that is integrated or customized.”

The State of Testing 2024 report found that despite the many advantages augmented and automated testing offer, the technology is still not close to replacing manual testing.

Only 2-3% said that their organization has completely replaced humans with AI in the testing phases.

Salesas from Leapwork explained that AI-augmented testing makes the cognitive load smaller so product builders can be more productive in places that matter.

“It frees up time and resources in QA teams, speeding up the overall software development process,” Salesas said.

“It can also explore complex application paths more thoroughly than humans, so you catch a lot more bugs.”

Additionally, AI-augmented testing can also make sure companies meet compliance demands.

However, in the present day, these tools are failing. Salesas broke it down:

“I don’t believe we are anywhere near the heights of autonomous testing Nirvana that some people may be dreaming of.

“Sure, some testing tools can do things like self-healing scripts where the AI adjusts a test in line with minor app changes, but they’re not so effective that they can handle the complexity of most real-world applications without any human supervision”, Salesas said.

“Some level of human validation is going to be needed for the foreseeable future to ensure accuracy and relevance, and the responses from the companies we surveyed corroborate that.

“Think of it this way: humans are better off with AI, but by the same token, AI is better off with humans.”

Salesas believes that the ideal collaboration scenario is one where the human does the input, the AI does the middle work, and the human signs it off. Most of the work AI is better suited for will be repetitive tasks, while humans deal with higher-level testing activities that involve some critical thinking or creativity.

Why Humans Are Unlikely to Disappear from Testing Processes in the Future

Leapwork’s report reveals that over two-thirds of C-Suite executives (68%) say testing will need human validation for the foreseeable future, and almost every single IT Director (92%) agrees.

“I think history has shown more than a few times now that technology rarely eradicates job roles entirely,” Salesas said. “It changes them”.

Salesas said that people also worried that the advent of test automation would make manual testers redundant. That didn’t happen.

“AI is really powerful — more than people realize — but the thing about it is that while we’ve created agents, they don’t have agency. That’s an important distinction.”

AI and automation tools take their objectives from humans, and humans need to be there to decide what to automate, what not to automate, and how to create good testing procedures.

“If AI-augmented testing is a second pair of eyes reviewing what an AI app produces, then the human is like the manager or director who sits on top of that hierarchy.”

‘Don´t Let AI Run Loose In Your SDLC,’ HackerOne Expert Says

Josh Jacobson, Director of Professional Services at HackerOne, a cybersecurity company leveraging the talent of the largest global community of ethical hackers in the world, spoke to Techopedia about the issue.

“AI, like any tool and technology, needs to be applied intentionally and thoughtfully. One must be aware of not only its capabilities but account for its limitations if teams want to effectively improve their DevSecOps.”

Jacobson recognized that AI has significant potential to address repetitive and time-consuming tasks such as categorization, saving teams hours of work every month.

“However, AI largely is not yet ready to be trusted enough to accurately execute more complex tasks or conclusions, so humans remain essential for QA testing.”

Jacobson from HackerOne compared testing tools with grammar and spelling checkers. They “have been around for quite some time,  but still require due diligence from the end user”.

No serious developer would deny that AI will get better and better at coding — in all its stages. But at the present time, Jacobson said, the technology can do more damage than good.

“AI’s ability to evaluate code is still in its infancy — it lacks the discernment, contextual knowledge, and insight that humans provide.”

“Letting it loose within your SDLC [Software Development Life Cycle] is likely to create more problems than solve them.”

Jacobson added that human experts may bring more signal, but if AI is applied in a rush, it introduces more noise to an already noisy step in the SDLC.

The Bottom Line

Those who use AI tools daily are well aware of the state of the technology. Despite all the hype, they know that AI is still not ready. Furthermore, you might argue it will never be.

The key to unlocking AI’s power can still be found in a balanced human-machine relationship. Otherwise, going full-throttle into Investing in AI with the aim of increasing production, lowering costs, and replacing developers may cost more money in the long run.

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