AI: Revolution or Threat to Human Employment?

AI: A Blurred Line Between Human Expertise and Automation

The distinction between human expertise and results generated by artificial intelligence is becoming increasingly tenuous. During a recent stay in Trieste, a software developer offered a refreshing perspective on the evolution of the tech industry. The conversation naturally turned to the classic debate about AI and the threat it might pose to jobs. But is it really AI that is to blame, or is there a more complex reality at play?

Even among young professionals of Generation Z, concern is palpable, which somewhat shakes the initial optimism. Is AI a threat to the industry or simply a tool that saves time on repetitive tasks? Opinions on this matter vary widely.

It is impossible to predict with certainty whether developers, QA engineers, and designers will still have career opportunities in five to ten years. However, it is undeniable that AI tools are developing at a breakneck pace, and everyone is gradually being encouraged to integrate them into their professional routines. The crucial question is where the line lies between AI capabilities and human expertise, and how to approach this technology thoughtfully.

Quality vs. Speed of AI

As an advocate for the quality of digital products, one professional is convinced that quality is not just about ticking boxes: it represents an essential link between technology and human experience. Yet, in the industry, it is noted that engineers increasingly resemble hamsters running in the wheel of accelerated development.

AI tools have brought unprecedented speed to development. However, this rapidity can sometimes compromise quality. Major incidents caused by AI agents, such as accidental database deletions, are no longer rare or amusing. Every experiment with AI should be approached with caution.

There are newcomers in the industry who place blind trust in AI agents, copying and pasting results without critical thinking. In the long run, this could harm the quality of digital products, an impact that few dare to address openly. It is imperative to develop a deep understanding of how to use this technology without being blinded by it. Self-education is crucial for everyone in this field. AI agents will only replace humans if the latter lose their ability to think critically.

Reluctance Towards AI Adoption

Distrust of new technologies is another end of the spectrum. A surprising trend has been observed: non-tech companies are slow to adopt modern technologies, and even some tech companies hesitate to use AI-driven tools.

It is understandable to be wary of AI, especially if a company does not have a well-established security policy. When a company uses AI tools developed by external vendors, the risk of data leaks is real. Even if a company is flexible enough to integrate AI agents, it is inadvisable to use a personal account to manage company code.

A QA engineer is currently exploring how AI can assist in writing test cases, charters, and bug reports, while manually refining the results. When writing prompts, only the necessary context is provided, without superfluous details.

This engineer continues to create his own stories and illustrations, although he uses an AI-driven grammar-checking tool. Ironically, he regularly discovers that his content is used in AI-generated articles.

He is convinced that the most creative ideas, such as those needed to develop a testing strategy, still come from human collaboration, even if AI can suggest points for a brainstorming session. The next level of AI proficiency involves learning how to provide enough context to an AI tool without compromising security, privacy, and authenticity.

Which Tasks to Delegate to AI?

Naturally curious about new tools, one professional is testing how AI can assist in the daily work of a QA engineer.

He remembers a time when everything was done manually: test cases were written in a spreadsheet or a test management tool, and code was typed line by line. Today, it is noted that some QA professionals do not hesitate to delegate these tasks to tools like Gemini, ChatGPT, or Claude. It just takes a keen eye to examine the results produced by AI agents.

If one merely copies and pastes, it is easy to miss certain subtleties. It is always possible to refine the output generated by AI: edit it, add points, reorganize, etc.

One professional would willingly delegate repetitive tasks, such as generating test cases and automating regression tests, to AI. However, he is convinced that exploratory testing is best performed by humans.

Yes, AI can guide in creating a test charter, for example. However, it cannot replace human empathy and critical thinking when evaluating the product. Therefore, it might miss edge cases and UX inconsistencies that a human eye and experience would catch.

Instead of being skeptical, it is advisable to make AI an ally. It saves a lot of time for senior developers, QA engineers, and designers. It can be an excellent support in the learning journey for mid-level and junior specialists. Ultimately, it is essential to be critical of the results provided by an AI agent. Blindly copying and pasting can lead to rookie mistakes and cause serious harm to a company.

Balance is vital in this journey with AI. It should not be relied on too much, but if it is underestimated, progress may not be quick enough (like that hamster in its wheel 🙂).

It is possible to check out this engineer's LinkedIn page to learn more about his background. With over 8 years in the tech industry, he has evolved from a tester to a strategist and quality engineer. He is ready to connect with teams seeking advice to improve product quality and testing. Right now, he is looking for a new role as a QA analyst, QA engineer, or QA manager.