Given the recent ChatGPT going rogue incident, they may have a point. Here’s the word;
Financial services organisations are under growing pressure to deliver software faster, but many are struggling to maintain confidence in software quality as AI increases the volume and complexity of software development. The findings come as financial regulators place increasing emphasis on AI governance and oversight, with supervisory expectations continuing to evolve as firms deploy autonomous AI systems across critical business functions. For a highly regulated sector where software quality is intrinsically linked to operational resilience, compliance and customer trust and reputation, the findings from Tricentis‘ 2026 Quality Transformation Report highlight a growing challenge:
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Nearly two-thirds (64%) of global financial services organisations release untested software code.
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30% say AI is creating more code than teams can realistically test.
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Leadership pressure to move faster encourages 30% of teams to release software before testing is complete.
AI-driven development widening the software quality gap
More than a quarter of financial services organisations (27%) say poor software quality would have its greatest impact by leading to security breaches or compliance failures, while the same proportion (27%) point to higher technical debt and maintenance costs. One quarter (25%) point to the loss of customer or partner trust.
The financial impact is also substantial. Nearly two-thirds (65%) estimate that poor software quality costs their organisation more than £372,000 annually, while almost one in five (18%) believe the annual cost exceeds £744,000.
AI adoption accelerating faster than governance readiness
At the same time, AI adoption is accelerating across the sector. Seven in ten (70%) financial services organisations have implemented AI across some or all software delivery workflows, while 80% trust AI agents to make software release decisions.
Yet that confidence is not matched by readiness: only 40% of organisations say they are very prepared to operationalise, govern and scale AI agents. While implementing AI agents within software development and testing is the sector’s highlighted IT priority over the next 12 months (33%), establishing governance and trust in AI systems (29%) ranks closely behind, highlighting the need for organisations to advance AI adoption and governance in parallel.
Growing gaps in readiness and release alignment
The governance challenge extends beyond technology. Only 38% of organisations say software developers and executives are aligned on what constitutes release readiness and high-quality software, highlighting the difficulties many firms face in establishing effective oversight as AI adoption expands.
“Financial services organisations face unique pressure to balance innovation, speed and control. AI is helping teams deliver software faster, but it is also increasing the volume and complexity of software being produced,” said Andrew Power, Head of UKI at Tricentis.
“The challenge is no longer simply deploying AI; it is governing AI at the speed it is being deployed. Just as cybersecurity became a board-level priority over the past decade, AI governance is becoming a strategic concern for business leaders. Organisations need AI-powered testing and quality engineering capabilities that can keep pace with AI-driven software development while maintaining trust, meeting regulatory expectations and strengthening operational resilience as adoption accelerates.”
To read the full Tricentis 2026 Quality Transformation Report, please download it here.
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