Speed Over Quality: 60% of Singapore Organisations Now Ship Untested Code, Tricentis Report Finds

Tricentis, a global leader in agentic quality engineering, today released the findings of its second annual Quality Transformation Report, which aims to understand the state of software delivery in 2026 and the challenges facing technology leaders. The survey reveals that 60% of organisations in Singapore have released software with untested code—a sharp increase from 47% reported in 2025—as a result of increased pressure for speed from leadership teams.

The 2026 Quality Transformation Report is based on a survey of over 2,500 global CEOs, CIOs, CTOs, VPs of Engineering, DevOps and Quality Assurance (QA) leaders, and software developers across various industries, including manufacturing, energy and utilities, retail, financial services, and the public sector. Of those surveyed, 500 respondents were based in Singapore.

The findings come amid a broader push in Singapore to scale practical AI adoption, deepen AI capabilities, and strengthen governance around enterprise AI use. As organisations embed AI more deeply into software development and business operations, Tricentis’ Singapore findings point to a growing challenge for organisations to ensure software quality, oversight, and release confidence keep pace with AI-enabled delivery.

In Singapore, the Study Found:

• Poor software quality continues to carry a significant financial toll: Nearly two-thirds (64%) of organisations in Singapore estimate that poor software quality costs them between S$641,325 and S$6,410,885 annually through outages, delays, and operational disruption.

• Software quality gaps are widening despite growing AI confidence: Financial services organisations are the biggest offenders, with 71% admitting to releasing untested code, while 36% say leadership pressure to accelerate delivery is driving the issue.

• AI and automation tools are now deeply embedded across the software development lifecycle: 89% of organisations are using three or more AI or automation tools across the software development lifecycle, reflecting rapid enterprise-wide adoption as businesses look to improve productivity, accelerate delivery, and scale software innovation.

• Organisations are increasingly trusting AI to make high-stakes software delivery decisions: 84% of Singapore organisations say they trust AI agents to make software release readiness and delivery-impacting decisions without human oversight, signalling growing executive confidence in autonomous AI-driven operations.

• Businesses believe they are ready to operationalise and scale autonomous AI testing: 82% say they are prepared to operationalise, govern, and scale AI agents and autonomous testing across the software development lifecycle as enterprises accelerate investments in AI-led software delivery.

• AI implementation and improving release confidence are leading IT priorities for 2026: Nearly one-third (32%) of the respondents identify implementing AI agents within software development and testing as a top IT priority over the next 12 months, while 31% say reducing delivery risk and improving release confidence are important.

Damien Wong, Senior Vice President, APAC (Asia-Pacific & Japan), at Tricentis, Comments:

“Singapore is moving quickly to invest in and scale practical AI adoption, from AI-assisted software development to more autonomous, agentic systems. But as organisations build new AI capabilities, the research highlights a growing disconnect between organisations’ confidence in AI and their ability to consistently deliver high-quality software. Traditional quality assurance pipelines were built for a world where code was written, reviewed, and tested by humans under known conditions. However, as AI accelerates software development, organisations are now producing code at a pace that many existing governance and testing frameworks were never designed to support.

As the volume of AI-generated code increases, so too does the risk of hidden defects accumulating and surfacing only after deployment—where they are significantly harder, more costly, and more damaging to resolve. Software testing and quality assurance are increasingly becoming boardroom issues, much like cybersecurity did in previous years. As Singapore businesses deepen AI adoption, quality, governance, and oversight must scale at the same pace. With software failures carrying growing financial, operational, and reputational consequences, businesses can no longer rely on conventional testing approaches alone. The findings reinforce the need for stronger governance, continuous validation, and modern software quality frameworks that embed accountability, compliance, and trust across the entire AI-enabled software development lifecycle.”