Software companies face tremendous pressure to deliver products quickly, but too many AI-based tools create low-quality code.
Therefore, “the software testing space is at a breaking point.” At least, that is the stark warning from SmartBear CEO Frank Roe.
According to the industry insider, the crisis is precipitated by two interrelated problems.
Firstly, “the increasing and immense business pressure on teams to continue to deliver software code faster amidst fierce competition and a developer shortage,” Roe wrote in a recent analysis.
Secondly, the unstoppable rise of generative AI.
“Although the promise of AI-powered development tools is undeniable, a crucial element is missing from the conversation around these AI assistants, the increasing flood of low-quality code, with catastrophic consequences,” Roe stated.
CrowdStrike drama
The Microsoft/CrowdStrike outage in July was a stark reminder of the global dependence on software and the challenges an internet shutdown could cause to many banks, financial services firms and other companies, such as airlines, around the world.
Roe singled out a recent study which found that the U.S. is the nation that’s most economically vulnerable to an internet outage, with the cost estimated at a staggering $458,941,744 per hour.
“The overwhelming impacts of software failures are making headlines at an alarming rate, wreaking havoc on businesses and directly endangering lives,” he said.
“These problems include everything from failures in 9-1-1 dispatch systems to delayed care for patients who rely on optimized critical medical equipment in hospitals to threats to airline travellers who count on the accuracy of navigation and safety systems,” Roe wrote.
“With increasing dependence on software, the pressure on businesses remains intense, and these problems and disruptions continue,” he added.
Friend or foe?
Roe would like to focus the attention firmly on the rapidly evolving GenAI technology.
“Hailed as a game-changer, generative AI has undeniably transformed software development, but it’s important to remain aware of the potential complexities and risks it introduces,” he stressed.
As generative AI tools have lowered the barrier to entry for code creation and democratised software development, the foundation of our software-dependent world has come under threat, he continued.
“Limited oversight has led to an influx of subpar code, often riddled with bugs and vulnerabilities that enter the system.”
Roe pointed out that the increasingly common practice of having non-technical individuals create code exacerbates the issue because they may not understand the intricate nuances and potential downstream consequences of the code they’re creating.
“The lack of understanding about coding complexities and the necessity of rigorous testing is leading to a degeneration in code quality,” he explained.
According to Roe, this trend is evidenced by increasing reports of software failures, which are often linked to overlooked coding errors and inadequate testing.
“Studies have shown that as more people with limited programming experience contribute to codebases, the number of critical bugs and security vulnerabilities undergoes a significant increase,” he noted.
“The software industry is at a breaking point, facing a silent crisis that demands immediate attention.”
– Frank Roe
Roe said that, as the CEO of a global tech company, “I understand the immense pressure businesses face to stay competitive, and the subsequent pressure this places on our engineering and product teams.”
He called generative AI a powerful tool, catalysing increased productivity and automating repetitive tasks in development and testing.
Nevertheless, it also “poses potential threats to the foundation of software development, and is contributing to the generation of subpar code and heightened vulnerability to security threats,” Roe summarised.
He argued that AI lacks the ability to fully grasp the nuances and intentions behind complex software architectures, which can lead to suboptimal design choices.
Additionally, AI-generated code often suffers from poor documentation and readability, complicating future development and debugging efforts.
“Automated code generation has also resulted in less rigorous code review processes, increasing the likelihood of undetected errors and vulnerabilities,” Roe said.

Therefore, thoughtful use of generative AI, rooted in trust and transparency, is critical, he argued.
“This involves clearly communicating when AI is being employed, embedding responsible practices, and ensuring AI-driven code is thoroughly tested and reliable.”
Moreover, Roe thinks “this approach helps build confidence in AI tools among developers and end users, ensuring AI enhances rather than compromises the quality and integrity of software.”
Finally, for the industry veteran it is also important to ensure you are using generative AI to solve real customer problems, making feedback and transparency with customers critical.
In other words, by understanding AI’s limitations, developers can capitalise on its strengths while mitigating its risks, Roe stressed.
“Creating code that drives the apps and software we have all grown accustomed to is a complex and complicated process,” he added.
“This requires a human-centric approach, where developers maintain ownership of the code, validate outputs rigorously, and prioritise quality.”
Testing
Because of the speed at which teams are asked to release software, they need to embed quality earlier in the process, Roe said.
“This must start during the initial design and planning stages rather than being addressed solely during testing, ensuring teams identify and mitigate potential issues before they escalate.”
He is convinced there needs to be more comprehensive test coverage, now more than ever before, meaning thoroughly testing all possible scenarios, including interactions between different components.
“The immense pressure to deliver quickly and economically is leading to shortcuts and compromises that jeopardize the very foundation of quality work,” he warned.
Roe made a case for standardized, integrated solutions such as unified coding practices and consistent testing frameworks that prioritize both efficiency and high-caliber code.
“Standardisation helps maintain consistency and reduces errors across different teams and projects,” he noted.
“Integrated solutions enable seamless collaboration, ensuring that every aspect of the software development lifecycle — from design to deployment — is aligned with the highest standards.”
QA teams
Finally, Roe was keen to stress that the power of AI does not diminish the importance of experienced development teams.
“We need to use AI to streamline processes, not replace human judgment and critical thinking. AI can handle repetitive tasks, identify patterns, and suggest optimizations at a scale and speed that humans alone cannot match,” he said.
“The deeper understanding of context, project goals, long-term implications, creative problem-solving, and ethical considerations that experienced developers bring are irreplaceable, however.”
Roe added that by combining AI’s capabilities with human expertise, we can achieve a balance that enhances productivity while ensuring superior quality.
“The software industry is at a breaking point, facing a silent crisis that demands immediate attention,” he warned.
“Prioritizing software quality is not just an option; it is a necessity to safeguard the future of technology,” Roe said.
“We have had several wake-up calls, emphasizing the need to place software quality at the forefront. Compromising on this aspect is a risk we cannot afford to take,” he concluded.
“It’s time for a revolution in software quality.”
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