The Role of Software Quality Assurance in a Changing World of AI

Software Quality Assurance (SQA) or SQA Engineering is one of the most crucial positions in any software development team. These professionals ensure that the product meets the required quality by thoroughly understanding the requirements, collaborating with developers, and utilizing project management and various testing tools. They follow Agile Scrum methodologies to manage the entire process—from the beginning to the end of the project—ensuring the delivery of a high-quality product. As a result, SQA Engineers play a critical role in a team’s success.

Becoming an SQA Engineer is a high-demand, well-paying career, with annual salaries often ranging from $70K to $100K in the United States. However, recent changes in the industry, largely driven by the rise of artificial intelligence (AI), are reshaping the landscape.

The Challenge in SQA Today

Many SQA Engineers are underutilized because they are primarily performing manual testing. Manual testing is critical in ensuring the application meets the required standards and fulfills business needs. It allows testers to simulate the actions of actual users, verifying that the application behaves as expected.

However, a significant issue arises when manual testers are expected to also take on automation testing without being given adequate time or resources. Automation is essentially coding and can replicate user actions such as filling out forms, clicking buttons, or submitting data. But it requires time—something many teams do not account for.

Leaders often underestimate the time required for proper automation testing, resulting in rushed timelines. Additionally, Graphical User Interface (GUI) testing is becoming less prevalent as backend API-driven testing is becoming the norm. Backend automation, while simpler than GUI automation, still requires effort, tools, and skills that many QAs may not have the opportunity to develop, as they are often overburdened with manual testing.

The Role of Automation in Ensuring Quality

Effective automation is crucial to ensuring the long-term quality of an application as it scales. Without it, maintaining consistent quality becomes challenging, particularly as the application grows in complexity. Tools like Postman, REST API, ReadyAPI, and Cypress are widely used for backend automation, but the problem remains that sufficient time is rarely allocated for their use.

Automation demands focus, and teams often neglect to create dedicated automation roles. This lack of specialization is one of the reasons why many projects fail to implement automation testing effectively.

The AI Revolution in Software Testing

AI is now transforming the role of SQA Engineers, especially those who lack traditional coding backgrounds. While many QA professionals possess a strong quality mindset, they may not have the coding expertise necessary for automation. This is where AI steps in.

AI can automate many of the mundane tasks previously done manually, such as writing test cases, generating test documentation, and even drafting presentations. With AI, QAs can get up to 70% of their work done faster. For instance, AI can:

? Automatically write test cases based on the requirements.

? Create detailed test documentation by analyzing screenshots or input data.

? Generate Excel reports and presentations based on structured data.

By utilizing AI, the time spent on these tasks can be drastically reduced. What used to take two days can now be completed in just two to three hours.

Adapting to AI in the SQA Role

Despite the advantages AI offers, many QAs have been reluctant to adopt these new tools, often resulting in job losses. As employers recognize the efficiency AI brings, they are looking for professionals who are willing to embrace these technologies. Many manual testers are being replaced or their roles outsourced to offshore teams where automation can be done more cost-effectively.

To stay competitive in this evolving market, QAs must be proactive in learning and integrating AI into their workflows. AI is not just a tool to improve speed but also an opportunity to redefine the responsibilities of an SQA Engineer. The nature of the role is becoming more dynamic, with QAs expected to take on a variety of new tasks.

The Future of SQA

The future of SQA lies in adopting AI and understanding its role in automation testing. Those who fail to adapt to these changes risk becoming obsolete in a fast-moving industry. My next post will provide a detailed strategy on how you can transform your career and stay ahead of these changes.

Stay tuned for more insights and guidance on navigating this evolving landscape.

Thank you,

Shiblu Ahmad?

Inventor of Private Bootcamp?

Founder, TS4U IT Engineering Bootcamp?

Founder, Bootcamps Hub

Founder, PMCRM Hub

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