Applause has released the results of its third annual State of Digital Quality in AI Survey, revealing that, despite widespread investment in AI, only a third of organisations employ rigorous testing practices like red teaming to reduce risks, and just over half leverage productivity-boosting generative AI (Gen AI) tools in software development. Over 70% of developers and QA professionals surveyed said their organisation is currently developing AI applications and features, with 55% stating that chatbots and customer support tools are the main AI-powered solutions being built.
The global survey of more than 4,400 independent software developers, QA professionals and consumers explored common AI use cases, tools and challenges, as well as user experiences and preferences. The key findings revealed that many organisations are not embedding the most effective QA measures into the software development lifecycle (SDLC), dramatically reducing quality and ROI.
For example, over half of the software professionals surveyed believe Gen AI tools boost their productivity significantly – as high as 49% to 74%. Yet, 23% of software professionals say their integrated development environment (IDE) lacks embedded Gen AI tools. A further 16% aren’t sure if the tools are integrated with their IDE, while another 5% claimed that they have no IDE. Regardless, GitHub Copilot (37%) and OpenAI Codex (34%) are still the AI-powered coding tools of choice.
AI testing needs the human touch
With the rise of agentic AI, which makes decisions and performs actions autonomously without human oversight, rigorous testing throughout the SDLC is more critical than ever. Human intervention provides the most effective way to mitigate inaccuracy, bias, toxicity and other potential harms. The survey revealed the top AI QA activities that involve human testing include prompt and response grading (61%), UX testing (57%) and accessibility testing (54%). Humans are also essential in training industry-specific or niche models; 41% of developers and QA professionals lean on domain experts for AI training. However, only 33% of developers and QA professionals employ red team testing, an adversarial testing methodology and best practice to help mitigate the risks.
Consumer issues persist
Although businesses are investing heavily in AI to enhance customer experiences and reduce operational costs, flaws are still reaching users. Nearly two-thirds of consumers using Gen AI in 2025 reported they encountered some sort of issue with the experience, including biased responses (35%), hallucinations (32%) and offensive responses (17%). Within the past three months, only 35% reported that they have not encountered any problems using Gen AI. That said, 78% of consumers stated that multimodal functionality is important to them in a Gen AI tool, compared with 62% last year. The survey also found that Gen AI users are fickle with 30% having swapped one service for another, and 34% preferring different Gen AI services for different tasks.
“The results of our annual AI survey underscore the need to raise the bar on how we test and roll out new generative AI models and applications,” said Chris Sheehan, EVP of High Tech & AI, Applause. “Agentic AI is ramping up at a speed and scale we could hardly have imagined, so the risks are now amplified. Our global clients are already ahead of the curve by baking broad AI testing measures into development earlier, from training models with diverse, high-quality datasets to employing testing best practices like red teaming.”
Sheehan continued, “While every generative AI use case requires a custom approach to quality, human intelligence can be applied to many parts of the development process including model data, model evaluation and comprehensive testing in the real world. As AI seeps into every part of our existence, we need to ensure these solutions provide the exceptional experiences users demand while mitigating the risks that are inherent to the technology.”
