According to a recent survey, automation is an integral part of the testing activities of around 43% of companies, and around 23% of companies are thinking in favor of it. This is why it is important to discuss test automation and how the role of manual testers and Quality Analysts is transformed along with it.
Table Of Contents
Role of a Quality Analyst in Testing Transformation
Before diving in, let’s first look at a Quality Analyst’s daily work life and responsibilities.
Test Planning and Design
Writes clear, detailed test cases based on the feature requirements. The team then reviews these to ensure everyone is aligned and the test coverage is complete.
Continuous Testing During Development
As development progresses, Quality Analysts test features at every checkpoint to catch issues early. This often involves running a mix of manual and automated test cases to validate new functionality in real-time.
Test Execution and Bug Reporting
Once development is complete, test cases are executed to validate the feature end-to-end. Any issues found are documented as bug tickets with detailed steps to reproduce and shared with the development team for resolution.
Regression and Re-Testing
After fixes are applied, the same test cases are re-executed to confirm the issues are resolved. Quality Analysts also run regression tests to ensure that recent changes haven’t unintentionally broken existing functionality.
Automation and Pipeline Monitoring
Quality Analysts monitor CI/CD pipelines closely to ensure automated tests run as expected. They investigate the root cause of failures and collaborate with developers to fix them promptly.
Production Monitoring
Even after release, the Quality Analyst’s role continues. They monitor the live product to quickly detect and report any issues users might face in the real world.
Current Challenges and Pain Points for QA Analyst
Quality Assurance is expected to reach every corner and turn every stone. Naturally, the challenges of the job are just as big as the expectations. Here are some of the practical problems that Quality Analysts often face:
- Lack of Time for Automation
The expectation to automate everything is high, but in reality, Quality Analysts are often pressed for time due to tight release cycles and competing priorities. This is especially true when the automation tools they use are legacy tools that require almost as much effort as manual testing.
- Test Maintenance Overhead
As test suites grow, even small changes in the application can require updates across dozens of test cases, turning maintenance into a full-time task. This is precisely why choosing test automation platforms with self-healing capabilities is important.
This Reddit thread highlights how common and relatable these issues are among Quality Analysts and testers:
- Quality Assurance Not Integrated Into the Development Culture
Quality Analysts are often treated as a checkpoint at the end of development rather than a shared responsibility across the team, leading to isolation and a lack of collaboration.
- Uncontrollable or Unstable Test Data
Quality Analysts frequently struggle with inconsistent or unavailable test data, which makes it hard to validate scenarios reliably and repeatedly.
- Incomplete or Unclear Requirements
Quality Analysts often work with acceptance criteria that are either missing, vague, or open to interpretation, leading to mismatched expectations and last-minute changes.
- Cross-Platform Testing Complexity
The need to test across a wide matrix of devices, browsers, operating systems, and their versions can be overwhelming and resource-intensive, especially when users still use older versions.
- Uncertainty in Upskilling
With rapidly evolving tools and technologies in testing, it’s hard for Quality Analysts to decide which skills or frameworks to prioritize for career growth or to meet the team’s needs.
Before diving into the next section, quickly brush up on automated testing.
How Does Test Automation Help Quality Analysts?
Minimal Learning Curve
One bottleneck that many teams face when switching to automation is upskilling. With an automation platform that supports codeless testing and where Agentic AI enables autonomous testing from test generation to maintenance, Quality Analysts can contribute without learning complex scripting languages. Quality Analysts can grow into automation roles without pausing their day-to-day work for long training cycles.
Speeds up Testing Process
Legacy automation platforms often behave like a second development environment. Codeless automation testing tools eliminate the need to write scripts manually, making it easier to create tests using natural language, such as plain English. Nowadays, many platforms have Agentic AI capabilities that analyze the application, suggest test steps, and generate test cases based on user flows.
Automated Test Maintenance
Anyone who’s worked on a growing test suite knows the pain of fixing dozens of broken tests after a UI update. AI-powered self-healing in modern automation platforms can detect UI changes and automatically adjust the affected locators or test steps without human intervention. This self-healing capability lets QA Analysts focus on real quality issues rather than constantly patching old tests.
Effective Collaboration
Modern test automation platforms make tests and results easily accessible to everyone in the team, and teams can also collaborate on these platforms. These platforms often have native integration with bug tracking and communication platforms like Jira and Slack. They also provide shared dashboards and real-time reports, making collaboration even better.
Test DATA & Test Environment Management
Agentic AI can assist in identifying the right test data patterns based on application behavior and even auto-generate or mask data when needed. Combined with cloud-based test environments, Quality Analysts can simulate real-world scenarios more reliably, reducing the dependence on flaky or inconsistent test data from backend teams.
Test Coverage
When requirements are vague, Quality Analysts spend a lot of time figuring out what to test. AI can bridge that gap by learning from historical test cases, user behavior, and past defects to recommend what areas need coverage. It can also validate test cases against application changes and flag gaps early, reducing the back-and-forth between Quality Analysts and product teams.
Cross-Platform Testing & Test Prioritization
Testing across every browser, OS, and device is unrealistic without a scalable solution. Cloud-based platforms offer instant access to thousands of real devices and virtual environments, eliminating the need to maintain local device labs. Agentic AI can prioritize tests based on usage data, helping Quality Analysts focus on the most critical combinations instead of testing everything manually.
Are you aware of the eight essentials required to move to automated software testing if you plan to switch to automation?
How Does AI Transform the Role of Quality Analyst?
With AI-powered platforms, testing is no longer about writing and maintaining complex automation scripts but about deciding what to test and why. Instead of spending hours on repetitive tasks, Quality Analysts can now guide AI agents to generate and run tests just by describing user flows or business goals. AI handles the heavy lifting like test creation, execution, and maintenance, so Quality Analysts can focus on high-impact work, such as understanding user behavior, uncovering edge cases, and improving product quality.
Tools with Generative AI and Agentic automation capabilities optimize the workflows of Quality Analysts. By automating the routine, these tools give Quality Analysts more time for strategic thinking and collaboration. But AI still needs guidance. It isn’t plug-and-play, and it won’t know what matters to the business without direction. That’s where Quality Analysts shine, bringing in their deep product knowledge and user empathy to ensure the AI tests what truly matters.
How Testsigma Helps in Achieving Test Automation KPIs
Testsigma is a GenAI-powered, codeless test automation platform that empowers quality engineering teams to create, manage, and execute automated tests up to 10X faster. It is a unified platform to test web, mobile (iOS and Android), desktop applications, Salesforce and other packaged apps, APIs, and databases. With its intuitive interface and powerful Agentic AI capabilities, Testsigma helps teams deliver high-quality software at speed, without the complexity of traditional automation tools.
Key Features:
No-Code Test Automation
Create, manage, and run automated tests using simple English, making it easy for both technical and non-technical team members to contribute.
End-to-end Coverage
Testsigma supports cross-browser, cross-device, accessibility, and visual testing to help you ensure a consistent user experience across all platforms and users.
30+ Native Integrations
It seamlessly integrates with popular CI/CD, bug tracking, and communication tools like Jira, Slack, Jenkins, and GitHub to fit right into your existing workflow.
Conclusion
While automation can significantly optimize a Quality Analyst’s efforts, it’s essential to have a clear strategy and choose the right automation platform. A codeless platform with autonomous capabilities, like self-healing tests, can save Quality Analysts from repetitive tasks such as constantly fixing broken test scripts. Legacy tools, on the other hand, often lack these features and require QA Analysts to write code, manually create, run, and maintain tests. So, what’s the point of automation if it feels like manual testing in disguise? In a fast-paced development environment, testing needs to keep up. So yes, automate your tests, but do it with the right tool.
FAQs
No, you don’t need programming knowledge if you use no-code test automation platforms like Testsigma. But legacy tools and traditional automation frameworks do require coding skills.
Yes, no-code automation platforms have a minimal learning curve, and AI-powered tools can automate end-to-end testing without the need for extensive training.
Yes, automation skills are in high demand as more companies adopt automated testing. Learning it can open up better Quality Analyst roles in modern, tech-driven teams.
Yes, platforms like Testsigma support smooth migration from manual to automated tests, and their support teams will actively assist you throughout the process.
