Amidst numerous notable outages affecting global infrastructure, only 16% of organisations believe their current software testing practices are efficient, according to a recent survey by Leapwork.
This survey highlights that the increasing adoption of Artificial Intelligence (AI) is contributing to this problem. The findings are based on responses from 401 senior and technical professionals from the US and UK.
The survey revealed that 85% of the respondents have integrated AI applications into their tech stacks over the past year. However, most of these organisations (68%) have faced challenges related to the performance, accuracy, and reliability of these AI applications. The lack of effective testing processes has negatively impacted the usability of AI applications. For C-suite executives, who made up half of the survey sample, the perception of inefficiency is even higher at 73%, compared to 62% for software engineering or technical leads.
"For all its advancements, AI has limitations, and I think people are coming around to that fact pretty quickly," said Robert Salesas, CTO at Leapwork. "The rapid automation enabled by AI can dramatically increase output, but without thorough testing, this could also lead to more software vulnerabilities, especially in untested applications. It makes sense that C-Suite executives would be especially sensitive to this because of the implications for customer experience and negative publicity. There's an opportunity here for cross-industry collaboration to ensure more testing tools are up to scratch for the challenges of the modern world where AI apps are more and more widespread."
Respondents pointed out that the rapid advancement of AI applications has led to challenges when incorporating them into enterprise workflows. The most common issues identified were integration failures (21%) and security vulnerabilities (23%). Additionally, three top challenges have been highlighted while attempting to integrate AI into software:
- Resistance to change within the organisation (20%)
- Inconsistent performance and reliability of AI applications (19%)
- Managing the rapid pace of AI advancements and updates (19%)
As a result, 77% of organisations now regard AI testing as essential. Despite this, significant gaps remain in testing resources and practices. Nearly a quarter (24%) of organisations do not have a dedicated team or individual responsible for testing AI applications, and 26% lack a commercial testing platform. Approximately 30% believe their existing testing processes are inadequate for ensuring reliable AI applications.
"There have been too many outages this year alone, many of which affected millions of customers for big brands. We've been given a wake-up call no one can ignore," remarked Christian Brink Frederiksen, CEO of Leapwork. "What makes digital infrastructure today so tricky to test is the copious amount of complex, interconnected applications. A tiny error in one application could have a monumental cascading effect and shut down businesses. Whether big or small, all updates need appropriate testing, but many businesses have outdated, siloed approaches. It shouldn't be about testing one individual app – it should be about testing the entire user journey."
With AI now integrated into nearly every aspect of business operations, ensuring flawless performance has never been more critical. CIOs and CTOs need to recognise that the future of their digital infrastructure depends on moving beyond traditional, isolated testing methods. Adopting a holistic approach that thoroughly vets every application and user journey will be key to maintaining operational resilience and customer trust in the era of AI-powered solutions.
