The software testing landscape will significantly transform in 2025 driven by economic pressures, increasingly complex application ecosystems, and rapid technological advancements. The pressure to release faster while maintaining quality and managing tighter budgets means that quality assurance (QA) teams face growing demands that require strategic foresight and innovative tools. High-profile incidents like the CrowdStrike outage underscore how vital robust QA practices can be, where even minor code changes can trigger widespread business disruptions.
Below, we explore the key trends set to define software testing in the year ahead.
Author: Andrew Power is Head of UK and Ireland at Tricentis
Keeping up with accelerating digital innovation amidst economic pressure
As organisations balance the need to maintain their competitive digital edge against economic constraints and limited resources, we will see a growing requirement to do more with less. This will mean faster software development and more efficient software testing processes, pressuring software engineers to deliver high-quality applications and updates within ever-tightening timeframes.
Shorter release cycles mean QA teams face greater challenges with change impact analysis. Software quality intelligence will emerge as a vital tool, using AI to automatically evaluate code changes and highlight quality risks. This targeted approach reduces the need for mass testing, allowing QA teams to focus on areas with the greatest potential impact, saving time and resources while maintaining robust quality assurance standards under tight deadlines.
Test automation will also help to relieve both expectational and resource pressures, enabling teams to efficiently manage frequent and complex deployments without compromising quality. Test automation solutions that seamlessly integrate into DevOps pipelines will help organisations navigate heightened expectations and manage high workloads efficiently.
Cloud adoption and QA adaptation
As organisations accelerate their transition to the cloud, QA teams must adapt to hybrid testing environments that span on-premise, cloud, and multi-cloud setups. This shift introduces new complexities, requiring seamless management of diverse deployment environments to ensure consistent application performance. Moving test cases to the cloud and integrating tools like SAP Cloud ALM will streamline QA processes.
However, cloud transformation is not just a one-time project—it demands a fundamental operational shift to keep pace with increasingly rapid release cadences from SaaS providers like Salesforce, Oracle, and SAP. With enterprise applications nearing end-of-life for on-premise solutions, the pressure to adopt SaaS and modernise processes is mounting.
In 2025, this urgency will intensify as SaaS vendors accelerate their release cycles and customers seek to leverage the full benefits of SaaS agility. To stay competitive, organisations must embrace automation and AI at scale, enabling faster, more efficient testing to keep up with these evolving demands.Â
Driving efficiency and compliance
As the European Accessibility Act (EAA) comes into force in June 2025 to ensure equal access to digital products and services across the European Union, accessibility will gain greater importance in software development. To address these requirements, QA teams must integrate accessibility tests into DevOps workflows, while automated testing solutions that support the ARIA (Accessible Rich Internet Applications) framework will play a crucial role in meeting these standards efficiently.
Moreover, with data centres accounting for almost 4% of total EU electricity demand, lean, clean software code will increasingly represent a further area of focus. However, this is more likely to be driven by financial motivations than environmental concerns. By adopting a shift-left approach, where quality assurance is integrated early in development, companies can minimise inefficiencies, avoid unnecessary data accumulation, and build cloud-native applications that scale dynamically. More efficient IT systems reduce costs and mitigate risks, but also offer environmental benefits as a consequence.
Harnessing GenAI for testing
AI’s transformative impact on software testing will continue to expand, addressing some of the most persistent challenges, like improving efficiency, reducing costs and enhancing software quality. GenAI-powered tools will also enable non-technical users to participate in testing, democratising quality assurance across organisations through user-friendly, low-code platforms. A recent Tricentis study revealed that nearly 70% of organisations view AI-driven DevOps testing as ‘highly valuable’, particularly for risk-based testing, test case generation, and results analysis.
To unlock GenAI’s full potential, however, AI must be fully integrated across workflows rather than adopted in silos. Success will come from fostering a culture of continuous improvement, where incremental advancements compound over time, rather than expecting immediate, large-scale results. As regulatory guidelines tighten, continuous testing will also become a critical element of compliance, safety and efficiency.
Embracing change: Turning QA challenges into opportunitiesÂ
Economic pressures, rapid technological advancements, and the increasing complexity of digital ecosystems will require QA teams to adopt integrated automation, AI-driven testing, and agile cloud solutions to keep pace with shorter release cycles and rising quality expectations in 2025. Organisations that succeed will prioritise continuous improvement, aligning testing practices with broader digital transformation goals while fostering collaboration across teams and tools. By embracing these shifts, QA leaders can turn challenges into opportunities, ensuring their systems are resilient, compliant, and positioned to drive innovation and long-term value.
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