When AI Will Replace Manual Testers
Artificial intelligence is quickly changing how many industries operate, and software testing is no exception. With its ongoing evolution, AI is significantly redefining the way we handle quality assurance. It is now capable of executing test scenarios and interpreting results with impressive speed and consistency. Because of this fast artificial intelligence progress, we hear that “AI will replace manual testers,” and that it alone can handle product testing.
But is that really the case? And as a QA company, we can’t stay silent on this topic and want to share our perspective. So, let’s find out together!
AI vs. Human Testers: Advantages Compared
AI offers significant advantages in speed and scalability when applied to software QA, but it does not replace the need for human testers. In our experience working with a wide range of digital products, including those powered by AI, we observe that each approach has distinct strengths.
To provide a clearer picture of their respective roles, we’ve prepared a side-by-side comparison of AI and human QA engineers based on real testing scenarios and what we see in practice every day.
AI Also Needs to be Tested
We’ve looked at where AI excels and where manual testing still has a clear advantage. Let’s also discuss something just as important: AI needs to be tested, too, before it’s released to the market.
This is crucial to ensure AI behaves reliably, ethically, and in line with user expectations – not just technically, but in ways people can trust. Recent research published in The Guardian found that nearly 60% of people still don’t fully trust AI-driven tools and decisions. [1] They remain skeptical of artificial intelligence because it can produce outdated, inaccurate, or contextless results. That’s why, to prove AI systems are safe and ready for real-world use, they require rigorous testing.
At QATestLab, we provide both AI Testing and AI Agent Testing services, helping teams validate how their systems react in unpredictable environments, handle user interactions, and maintain logic over time.
Real Cases of AI Failures
Air Canada’s AI-powered chatbot misinformed a customer about bereavement fares, suggesting they could book a full-price ticket and request a partial refund. In reality, such a policy didn’t exist. The customer followed the advice but was denied a partial repayment. The airline claimed the chatbot wasn’t an official representative, but a Canadian court disagreed and held Air Canada responsible for the false information provided by its AI. [2]
A chatbot operated by the UK delivery company DPD went viral after it began swearing at users, mocking the company, and even composing sarcastic poetry. The incident was caused by a faulty update that allowed the chatbot to generate unsupervised responses, leading to public backlash and media attention. [3]
McDonald’s used the AI chatbot “Olivia” from Paradox.ai to assist in recruiting. Security researchers discovered that the admin panel could be accessed using the default password “123456,” exposing over 64 million job applications. This raised major concerns about data privacy and platform security. [4]
Why Manual Testing Is Essential When Validating AI
At QATestLab, we have extensive experience testing AI-powered products, and we know better than anyone that manual testing is absolutely essential for verifying how AI systems truly work. Here are some key reasons:
- Context matters: Only humans can judge whether AI’s answers fit cultural, social, or emotional contexts.
- Quality of interaction: Human testers assess how natural, polite, and user-friendly AI’s responses feel in real conversations.
- Ethics and bias: People can detect biased or unethical outputs that automated scripts often miss.
- Edge cases and unusual scenarios: Testers explore unexpected inputs or rare situations to see how AI handles them.
- Visual and aesthetic evaluation: Humans evaluate whether AI-generated images or designs look appealing and on-brand.
- User experience: Real users can tell if an AI tool feels intuitive, smooth, and pleasant to use.
- Unpredictable AI behavior: AI sometimes produces unexpected or nonsensical outputs. Humans identify and analyze these issues to prevent surprises.
That brings us to the question: How can AI replace manual testers… if we still need manual testers to check the AI itself? It’s a pretty solid argument for why the human role in QA isn’t going anywhere any time soon.
What’s the Right Approach?
We’ve seen what AI can do and where it remains limited. We’ve also made it clear that manual testing still plays a crucial role in evaluating context, quality, and user experience.
In our view, the most effective way forward it’s not about choosing between AI-powered tools and manual QA, it’s about combining them.
A hybrid testing strategy leverages the strengths of both:
- Automation and AI for speed, scale, and repetitive tasks
- Human testers for flexibility, critical thinking, and user-centered insight.
This balanced approach helps teams deliver products to market faster without sacrificing product quality or user trust. We apply the same principle in our QA practice to make sure every software we test is reliable, accurate, and ready for real use.
How Manual QA Roles Will Evolve
AI brings substantial benefits to software testing and is now an essential part of the process. As a result, manual testers must adapt and learn to work alongside these technologies. It is a shift that is already redefining the role of human QA engineers. Let’s explore what they should take into account:
Understanding the AI and automation principles
Working alongside AI tools requires a solid understanding of how they function, what influences their outputs, and where they can go wrong. This knowledge helps testers make informed decisions, validate results, and fine-tune testing strategies together with AI.
Applying critical thinking in testing
AI can optimize test coverage, but it doesn’t know what’s truly important to users. Testers should shift their perspective from “what to test” to “why it matters”, validating user journeys, critical flows, and real-world needs.
Collaboration with product teams
AI can help automate execution, but it lacks awareness of business context. Manual testers should work closely with product managers to understand user needs, priorities, and success criteria. This ensures testing efforts focus on what truly matters to the end user and the business.
Openness to new tools and methods learning
The testing tool set is evolving rapidly. Thus, manual testers should stay open to experimentation, embrace new platforms, and adopt modern practices to stay relevant and drive innovation.
Deepening expertise in non-functional testing
While AI can’t match human intuition, manual testers should deepen their expertise in exploratory, usability, accessibility, and performance testing, where human judgment is critical.
Monitoring ethical risks and bias in AI systems
AI systems can introduce bias or exclude underrepresented user scenarios. Human testers are responsible for ensuring fairness, inclusivity, and ethical integrity, especially in sensitive domains like healthcare or finance.
Shifting toward a strategic quality role
Manual testers are evolving into quality partners, combining human insight with AI capabilities. Their role is to guide, evaluate, and shape quality in a broader, more proactive way.
Conclusion: Is Manual Testing Still in the Game
No matter how advanced the tools become, human insight, creativity, and empathy ensure that software truly works for real users. If the testing relies solely on AI, your product will ultimately be prepared for machines rather than real users.
At QATestLab, we believe that the future of QA lies in hybrid testing – a thoughtful combination of human expertise and AI-driven tools. It allows us to ensure your product is tested thoroughly, efficiently, and in line with user and business expectations.
Understanding the benefits of AI and the importance of integrating it into modern QA workflows, we continuously enhance our knowledge and practices to work effectively with both AI-driven tools and classic testing methods. If you’re looking for a QA partner who understands both innovation and quality, we’re here to help. Call us today to start the right testing strategy for your software, including AI products and AI agent solutions.
And if you’re curious about which other industries might actually be at risk of AI taking over, don’t miss our article: [5 Industries AI Could Replace Sooner Than You Think]. You might be surprised by the conclusions.
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