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The SaaS market is set to surpass $1 trillion by 2032, indicating a CAGR of 18.4% during the forecast period (2024–2032). This rapid expansion brings both immense opportunities and challenges for SaaS providers navigating intense competition, evolving customer demands, and innovative business models.
To stay ahead, delivering exceptional quality of products is critical. Quality Engineering (QE) has shifted from reactive to proactive, driving faster releases, reduced costs, and enhanced product stability. Modern QE practices like AI-driven automation, automation, and full-stack observability are transforming SaaS development, ensuring efficiency, scalability, and seamless user experiences.
By adopting these trends, SaaS leaders can future-proof their businesses, exceed customer expectations, and secure long-term growth in an increasingly competitive market. Let’s explore how these trends can position your SaaS product ahead of the curve.
QualityKiosk’s Top 6 Quality Engineering Predictions of 2025 for SaaS
Prediction 1: AI-Driven QE: A Strategic Imperative
AI is no longer futuristic—it’s a transformative force in QE, driving predictive analytics, defect detection, and test automation. At QualityKiosk (QK), we view AI-driven QE as a strategic imperative for SaaS companies to thrive in a competitive market. By 2026, over 80% of enterprises will rely on AI, solidifying its role in QE.
For example, a SaaS company launching a project management tool in 2024 used AI to predict risky code areas, prioritize tests, and catch defects early, saving 40% of testing time and ensuring a smooth rollout. In 2025, these capabilities will advance, enabling real-time adaptability to code changes for faster, more reliable releases.
For example, we collaborated with a SaaS workplace platform to transform its quality management approach. By shifting to a structured, outcome-driven QE roadmap and integrating shift-left practices, we optimized their DevOps processes. This resulted in an 81% boost in automation efficiency, a 60% reduction in test suite runtime, and a 20% shorter cycle time.
Prediction 2: Enable End-to-End Testing with automation in QE
At QK, we predict automation will be a core driver of QE by 2027, with the global automation market reaching $26 billion and growing at 23.1% annually. Powered by RPA, AI, and ML, automation automates end-to-end testing, enabling seamless execution, real-time insights, and faster feedback loops—critical for SaaS companies’ scalability and innovation.
We’ve witnessed this shift in action first hand. For instance, our collaboration with a leading Indian OTT platform serving 56 million users involved automating testing across 500+ devices. The outcome? A 50% faster time-to-market, 60% fewer production tickets, and a noticeable rise in app ratings. By 2025, automation will further optimize CI/CD pipelines, accelerating releases, improving quality, and driving customer satisfaction.
Prediction 3: Leverage Continuous Quality with Shift left and Shift right testing
QualityKiosk envisions that shift-left and shift-right testing will be central to QE by 2025, driving faster, higher-quality releases. Shift-left enables early defect detection, increasing test coverage by up to 70%, while shift-right focuses on continuous real-world monitoring in production for improved performance and customer satisfaction.
We’ve seen this in action with a San Francisco-based SaaS provider, where shift-left practices eliminated automation debt and enhanced QE with 40% improved coverage and 30% reduced defects, while AI-driven monitoring increased user satisfaction by 25%.
By 2025, we predict that these integrated strategies will be crucial for faster defect detection, better performance, and higher customer satisfaction for SaaS companies.
Prediction 4: Enhance Product Performance and Reliability with AI-powered, Full-stack observability
QualityKiosk predicts that by 2025, full-stack observability and AIOps will be essential for SaaS companies aiming for operational excellence and superior user experiences. These technologies provide real-time visibility from infrastructure to end-user interactions, enabling proactive issue detection, automated root-cause analysis, and continuous performance optimization.
For example, consider QualityKiosk leveraging Dynatrace’s AI-driven observability platform for a large-scale e-commerce product, offering real-time insights, anomaly detection, and quick root-cause analysis. This approach reduces downtime and enhances customer experience, especially during peak traffic like seasonal sales.
Looking ahead, we anticipate AI-powered observability and AIOps to further evolve, allowing SaaS companies to continuously optimize performance and ensure seamless service delivery.
Prediction 5: Simplify Test Automation with Low-Code/No-Code solutions
We see low-code/no-code test automation as a game-changer for SaaS companies by 2025. These platforms empower both technical and non-technical teams to create and deploy automated test cases, significantly reducing the barriers to automation. With intuitive drag-and-drop interfaces, tools like Watermelon are making test automation faster and more accessible than ever.
QualityKiosk leverages Watermelon for automated testing and reliability of mobile apps and web interfaces for SAAS products. This approach significantly reduces test development time by 30%, accelerates feature rollouts, and enhances the app’s overall reliability, ensuring a seamless user experience.
As we move forward, low-code/no-code platforms will accelerate releases, ensure higher-quality standards, and expand test coverage. According to Gartner by 2025, 70% of new app development will be powered by low-code/no-code platforms.
Prediction 6: Testing AI Systems
QK anticipates AI system testing will be essential to ensure unbiased decision-making and maintain accuracy in evolving data by 2025. AI-driven applications require continuous retraining and real-world testing to stay reliable and fair.
For instance, assume an AI-powered SaaS lending platform faced bias in loan eligibility assessments due to imbalanced training data. This can be resolved by leveraging an end to end AI feature testing process involving data validation, unit testing, integration testing, model validation, stress and load testing, robustness testing, fairness and bias testing, explainability, interpretability, and UAT to ensure fairness, accuracy, and compliance.
In 2025, as more and more SaaS products build AI features, testing and performance of these features and functionality will be critical. QK can provide end to end quality engineering services for AI systems.
Elevate Your SaaS Product Quality in 2025 with QualityKiosk’s QE Expertise
The future of SaaS development is shaped by the rapid evolution of Quality Engineering practices, including AI-driven QE, automation, shift-left/right testing, full-stack observability, low-code/no-code test automation, and AI system testing. Together, these trends drive agility, efficiency, and competitiveness in the evolving SaaS market.
At QualityKiosk, we don’t just follow trends—we lead the way in enabling SaaS businesses to meet their full potential with advanced Quality Engineering solutions.
Partner with QualityKiosk to elevate your SaaS products with world-class Quality Engineering solutions. Contact us today to learn more.
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