Quality Assurance (QA) has historically been the gatekeeper of software quality—writing and running test cases to catch defects before release. But many in the industry are now asking: “Is QA testing dying?” In an era of automated pipelines and AI-driven test solutions, companies are questioning the traditional role of QA engineers. This article explores why that shift is happening and what QA professionals can do to stay relevant.
Why People Say QA Is “Dying”
The Rise of Automation
Tools like Selenium and Cypress have been mainstream for years, but more recently, AI-driven solutions have started to handle tasks once considered exclusively “manual.” These new platforms promise to reduce human effort in writing, maintaining, and executing tests. As a result, managers and developers question the need for large QA teams:
Faster test creation: AI can auto-generate test scripts from user stories or plain English instructions.
Adaptive maintenance: When apps change, AI-based tools can update tests automatically, mitigating the pain of “test breakage.”
Shift-Left Testing
“Shift-left” is the practice of pushing testing responsibilities earlier in the development pipeline—in some cases, directly onto developers. Many dev teams now include robust unit, integration, and UI tests alongside their feature work. With each code commit, CI/CD tools run these tests automatically. This approach can make the specialized “QA tester” feel obsolete if the devs are handling most of the testing themselves.
Continuous Delivery Expectations
Software releases have accelerated from monthly or quarterly cycles to daily or even hourly deployments in some companies. This pace demands real-time feedback from automated checks. The days of large manual testing teams holding release cycles for extended test passes are fading.
Why QA Isn’t Really “Dead” (but Evolving)
It’s more accurate to say that “traditional QA roles are transforming,” not outright disappearing. QA as a discipline—ensuring software quality and reliability—remains crucial. The difference is in execution and skillsets:
Quality Strategy & Leadership: QA professionals increasingly serve as quality advocates or QA strategists, shaping test approaches and frameworks across teams rather than only running tests themselves.
Holistic Risk Assessment: While AI can automate test steps, humans provide nuanced risk analysis, understanding complex user flows, compliance requirements, and edge cases that might not be obvious to machine learning models.
Domain Expertise & Business Logic: Software is never just code—it’s a solution to a real-world problem. QA professionals with deep domain knowledge can better ensure that the software meets real business needs.
In short, quality is everyone’s job—but QA specialists can be the experts who enable that culture to flourish.
The New Skills QA Professionals Need
To remain relevant as the QA landscape changes, professionals should focus on these areas:
Automation Mastery
If you haven’t already, learn automation tools (e.g., Selenium, Cypress, Playwright) or adopt AI-powered test platforms. Even a fundamental grasp of coding concepts in languages like JavaScript, Python, or Java will open doors. Pairing that with the understanding of how AI-based testing solutions work can differentiate you from purely manual testers.
DevOps and CI/CD Integration
Understand DevOps principles and CI/CD pipelines—tools like GitHub Actions, Jenkins, or GitLab CI. Modern QA integrates testing steps seamlessly into the build and deployment process. The more you can script or configure your tests to run automatically with every commit, the more valuable you become.
Data Analysis & Observability
Modern QA often extends into production monitoring and observability. Familiarize yourself with tools like Datadog, New Relic, or Grafana to understand how code behaves in real-world environments. Being able to correlate user issues with test gaps is a big plus.
Domain Expertise & Cross-Functional Collaboration
Strong communication skills and business knowledge are increasingly valuable. By understanding the “why” behind a feature—user personas, compliance rules, or performance expectations—you can guide the automation strategies and ensure truly meaningful test coverage.
AI & Machine Learning Basics
Even if you’re not coding AI models yourself, get a grasp of how AI-driven test tools parse natural language, generate test cases, or identify flaky tests. That insight lets you make more informed decisions about test strategy and how to handle AI’s limitations.
4. How to Future-Proof Your QA Career
Become a Quality “Consultant”
Position yourself as a consultant within your organization who helps teams:
Select the right testing tools and frameworks
Implement best practices in version control and environment management
Measure quality metrics beyond pass/fail, such as user satisfaction or time to detect defects
When teams see you as an advisor rather than a person who just “checks off tests,” you remain integral.
Contribute to Development Standards
Work closely with developers to improve code quality at the source. This could mean:
Encouraging better naming conventions and testable architecture
Helping define acceptance criteria in user stories
Building or maintaining code coverage dashboards
When QA’s role includes proactive influence on engineering practices, you become embedded in the entire lifecycle, not just a gate at the end.
Champion Shift-Left Testing
Ironically, shift-left testing—often cited as a reason QA is dying—can also be your best friend. By leading the shift-left initiative in your company, you showcase your skills in:
Teaching developers how to write more robust tests
Identifying crucial integration points early
Setting up efficient test pipelines for every pull request
If you drive that cultural change, you’ll remain highly relevant, even if the “manual” tasks reduce.
Embrace AI Tools—Don’t Fear Them
AI won’t replace QA professionals if you use it to your advantage. Tools that translate plain English into test steps or automatically adapt to UI changes can free you from rote tasks, letting you spend more time on:
Exploratory testing
High-level test planning
Cross-functional collaboration
This is where human insight still outperforms any AI or automation script.
5. Final Thoughts: Quality Still Matters
Software releases may move at breakneck speed, and AI may automate many tasks, but quality and user experience are just as important—if not more so—than they’ve ever been. Organizations still need people who deeply understand the user’s perspective, risk mitigation, and effective test strategies.
The QA role isn’t “dying” so much as evolving into a more strategic, automation-driven, and domain-focused discipline. By learning modern tools, diving into domain knowledge, and leading shift-left initiatives, QA professionals can thrive rather than become obsolete.