Facing 2025: How to future-proof your QA career in an AI-driven world

AI will replace your QA job in 2025 if it mainly involves repetitive tasks.

If your job mainly involves tasks such as executing tests and logging bugs, actions that don't require high critical thinking, then it's time to rethink and upskill.

AI adoption has accelerated dramatically, with 72% of organizations using it in at least one business function, a significant jump from 50% in previous years. Of course, this includes the software testing industry as well. With this massive growth, AI and automation tools will handle most test execution and bug reports. And let's not forget that machines execute tasks much faster and better than humans. So, in 2025, it would be suicidal if you only equip yourself with common repetitive skills.

The good news is that true quality assurance goes far beyond repetitive checks. Risk analysis, creative test strategies, and deep product insights are skills that remain uniquely human, at least for now.

Let's discuss the QA tasks that are most at risk, why they're vulnerable, and how you can future-proof your career in an AI-driven world.

AI's Rapid Growth Surpassed Early Projections

AI adoption is no longer an experiment. Businesses are now starting to derive value from using it.

According to McKinsey's 2024 survey, 65% of respondents use generative AI regularly. That's nearly double the 2023 figure! So, it is reasonable to conclude that AI will no longer be a novelty in 2025 as more businesses will adopt it as part of their day-to-day operations. Companies like Google and Nvidia are investing heavily in it. And with their executives comparing its impact to electricity and the "iPhone moment.", it's safe to say that AI isn't going anywhere. At least not anytime soon.

So what software testing tasks has the rapid growth in AI impacted?

Repetitive Tasks Are the First to Go

Working as a QA engineer myself, AI has replaced some of my work, enabling me to focus on more high-order tasks that require critical thinking. And in essence, I've replaced testers whose job mainly involves repetitive tasks.

• Automated Test Case Creation: AI-driven frameworks can now analyze requirements, record user flows, and generate test scripts with minimal or no coding. These tools are especially effective for repetitive regression testing.
• Defect Logging: AI can also assist in drafting detailed bug tickets by just giving them enough level of context, data, conditions, and expected result.
• Test Data Management: AI tools can simplify creating, managing, and maintaining test data. They reduce manual effort in tasks like preparing data for automation.

AI performs well at pattern recognition, making it ideal for helping in structured tasks such as bug reporting and repetitive regression testing. Therefore, it is better for you to enter the 2025 with questions,

• How much of your daily work involves repetitive test execution and bug reporting?
• Are you applying in-depth critical thinking or mostly following a predefined checklist?

Critical Thinking Sets You Apart

Critical thinking and contextual risk assessment are what differentiates us from AI.

These two aspects of quality engineering are areas that are still challenging for AI to replicate. For instance, AI might be able to flag defects, but when it comes to judging which issue really matters and needs immediate resolution, humans still need to intervene. Contextual awareness is also key to conducting a good quality engineering process. Luckily, this is an area where we excel.

By understanding the context of your system, product, and customer, you can determine what's mandatory, what's good to have, and what's nice to have when performing testing.

The Path Forward: Adapt or Risk Obsolescence

Where does this leave you as a QA engineer on the cusp of 2025? There are a couple of recommendations that you could adopt to survive.

1. Become an expert with your products:  Even though you're not a product manager, knowing your products from end to end is more important than ever. This level of understanding helps you get a sense of awareness in terms of the risk and potential high-severity defect, something AI might struggle with.
2. Be more critical and risk-sensitive: Remember, what differentiates us from other people in testing (because everyone can perform testing, right?) is your ability to spot risk and think outside the box on the scenario that many people might miss. Most operational tasks like drafting test case steps, and creating bug tickets, will likely be delegated to AI while QAs focus on strategy. So, refine your risk assessment skills to stay relevant.
3. Be a good communicator: In an era where everything can be outsourced to AI, a lot of our time will be spent communicating with other project stakeholders. QA in 2025 will require enhanced communication skills, including proficiency in a universal language like English, along with the ability to persuade, negotiate, and engage empathetically.

If your role currently focuses on repetitive tasks, talk with your manager about taking on more challenging responsibilities. And if your organization can't accommodate this shift, it may be time for you to consider new opportunities that let you harness and grow your critical-thinking skills.

"AI Won't Replace Your Job, But Someone Who Knows AI Will." — Jensen Huang

Yes, AI will replace certain QA tasks in 2025. However, as technology progresses, QA engineers who focus on strategic, high-level responsibilities will remain in demand.

Despite AI's widespread adoption, I found many of my colleagues still underestimate its potential. From my personal experience, adopting large language models (LLMs) has doubled my productivity, at least.

By 2025, QA engineers may no longer need to write detailed test scripts manually. Instead, you'll guide AI on what to write, interpret its solution, and refine it—a shift from automation coding work to strategic oversight.

If you are still not utilizing AI potential in 2024, please consider adopting it now. No matter how excellent your skills are, you are always no match for someone who can utilize AI in terms of productivity. If you're still in doubt, I recommend reading "The Death of the Junior Developer" which illustrates how AI has reshaped developer roles, an equally relevant shift for QA professionals.

By leveraging AI to handle repetitive tasks, you can focus on what truly defines quality assurance, spotting hidden defects, assessing risks, and understanding the business context in depth.

Be open to new technology and have a mindset to learn, unlearn and re-learn.

References

1. McKinsey & Company (2024). The State of AI in Early 2024: Gen AI Adoption Spikes and Starts to Generate Value
2. McKinsey & Company (2023). The State of AI in 2023: Generative AI’s Breakout Year
3. PwC (2024). AI Jobs Barometer: How AI is Reshaping the Job Market
4. Sourcegraph. The Death of the Junior Developer
5. AIPRM (2024). 50+ AI Replacing Jobs Statistics 2024
6. Wholesale Investor (2024). The Profound Impact of AI on the Job Market in 2024: Disruption, Adaptation, and Opportunity