Modern QA: Balancing Technical and Soft Skills in the AI Era

In this edition of Tecknowledgy, Camille, Quality Assurance Engineer at Mercedes-Benz.io, shares how quality is becoming a shared responsibility across teams, why soft skills are becoming increasingly important alongside technical expertise, and how AI is helping QA evolve from validation to strategic enablement.

Camille Souza

Quality Assurance Engineer|MB.ioneer since July 2021

Fun fact:She is a gamer, being a huge fan of the God of War franchise.

Why quality starts long before testing

Working across QA, automation and DevOps has fundamentally changed how Camille sees her role.

Rather than treating quality as a final gate before release, she believes quality should be embedded throughout the entire delivery lifecycle.

Instead of quality being a final checkpoint, it becomes a shared responsibility that starts during planning and continues through development, deployment and production monitoring.

This shift has expanded the role of Quality Assurance beyond validating features after they have been built. Fast feedback loops, reliable delivery pipelines and observability have become just as important as testing itself because they allow teams to identify risks earlier and make better decisions throughout development.

AI is already accelerating part of this work. Tasks such as test case generation, data creation, code reviews and root cause analysis can increasingly be supported through AI-powered tools, helping teams focus more of their time on understanding risks and improving quality outcomes.

However, Camille does not see AI as a replacement for quality engineering.

The real power comes from pairing AI efficiency with engineering expertise.

Critical thinking, understanding customer impact and making informed risk-based decisions remain responsibilities that require human judgement.

The growing complexity of modern software systems

Modern quality challenges are no longer limited to validating individual applications. Today’s products often consist of interconnected services, cloud platforms, APIs and external integrations, creating ecosystems that are significantly more complex to understand, test and maintain.

For Camille, this complexity is one of the biggest sources of friction facing quality teams today. But technology is only part of the challenge.

Another common issue emerges when quality ownership becomes isolated:

When teams see QA as solely responsible for quality, defects are often discovered late in the process, leading to delays and rework.

Communication gaps can also create challenges when Product, Development, Operations and QA teams are working towards different priorities or measures of success.

Reducing this complexity is not simply a matter of adding more tests. Instead, Camille believes the key is shifting quality earlier into the lifecycle and making it a shared responsibility. When teams collaborate around quality from the beginning, they can identify risks sooner, reduce misunderstandings and avoid costly rework later.

The future of QA in an AI-driven world

As software ecosystems continue to evolve, Camille sees the role of QA becoming increasingly strategic.

Less time will be spent executing manual tests and more time will be spent understanding systems, defining quality strategies and helping teams manage risk.

The focus will move toward validating complex ecosystems rather than individual applications.

This evolution requires quality engineers to develop a broader understanding of cloud architectures, APIs, event-driven systems, observability and production monitoring. Understanding how systems behave under real-world conditions will become just as important as verifying individual features.

At the same time, AI will continue to automate repetitive activities such as test generation, reporting and defect analysis, creating more space for engineers to focus on decision-making and strategy.

As a result, Camille believes quality professionals will increasingly act as advisors within engineering organisations, where “QA engineers will act more as quality consultants and risk managers.”

Rather than functioning as a separate validation phase, quality will become further integrated into the software delivery process itself.

Balancing technical expertise and human skills

While technology continues to transform software development, Camille believes one thing remains unchanged: quality depends as much on people as it does on tools.

Technical expertise is essential for building automation frameworks, integrating CI/CD pipelines, designing effective testing strategies and creating scalable quality practices.

Yet some of the most important quality outcomes are not driven by technology alone: “Communication, collaboration, and critical thinking are equally important.”

Many issues are prevented long before a test is executed. Understanding business objectives, challenging assumptions, identifying risks and facilitating conversations across teams often creates greater value than any additional automation.

For Camille, the most effective quality engineers use technology to handle predictable and repetitive work while applying human judgement where context, creativity and collaboration are required.

Quality at scale is ultimately not just about engineering excellence. It is about helping teams make better decisions together.

A lesson for the next generation of quality engineers

Looking ahead, Camille encourages aspiring QA professionals to think beyond testing and focus on becoming versatile quality engineers.

Technical skills in automation, cloud technologies, APIs, observability, CI/CD and AI-assisted engineering will continue to grow in importance. These capabilities allow engineers to contribute directly to how modern software is built and delivered.

At the same time, long-term success often depends on softer skills: the ability to communicate clearly, influence decisions, collaborate across disciplines and explain technical risk in business terms.

Technology will continue to change. New tools will emerge and old practices will evolve. What remains constant is the need for curiosity, adaptability and strong problem-solving skills, and as Camille puts it: “The strongest QA professionals today are not defined by the tests they execute. They are defined by the value they bring in helping teams deliver better products with confidence.”