When discussing the future of the QA profession, it’s essential to consider the key trends shaping it. I would like to highlight two major directions: Manual and Automation QA. Just a decade ago, many conferences claimed that manual testing would disappear and be replaced by automation. However, five years have passed, and yet nothing has disappeared. On the contrary, the role of manual testing has strengthened and gained special value in the IT sector. Now, at the end of 2024, the situation has mostly remained the same. What is this trend about, and what is the reason for this?

The main reason is a misconception of automation’s role in testing.

When we hear the term “automation,” we might think of it in a stereotypical way. The most common assumptions are:

• testing something that already works
• fast and easy way to pass tests
• verifying existing functionalities
• performing the regression tests
• generating test reports for further analysis

Another words, automation doesn’t look for new problems; it simply checks that everything works as expected.

Manual testing, on the other hand, is always about exploration:

• searching for new issues
• analyzing new product aspects
• finding innovative approaches
• attention to detail
• and most importantly, CREATIVITY.

I firmly believe that without the detailed test scenarios created by manual testers, the efficiency and quality of automated testing would not be possible. Therefore, it’s more accurate to say that manual testing won’t disappear but will continue to evolve, adapt, and be enhanced with new tools.

Trends that are Shaping the QA Future

• AI and Machine Learning Integration

One of the most significant technological trends is Artificial Intelligence and Machine Learning. Large-scale models like ChatGPT are already actively deployed in multiple sectors. As AI and ML continue to evolve, we can expect more integration with the Internet of Things (IoT). ML is a subset of AI that focuses on building systems that can learn from data. Instead of explicitly programming rules, ML algorithms can learn from examples and data patterns to improve their performance over time. For software testers, ML can help in various ways, such as automatically generating test scripts, identifying anomalies in test results, or adapting testing strategies based on the changing nature of the software.

• The Increasing Importance of Cybersecurity

With the rise of cyberattacks and viruses, the focus on cybersecurity is becoming more and more relevant. Engineers should pay more attention to software security, which includes vulnerability testing and data protection. This makes cybersecurity a vital part of the profession that remains in high demand.

Detailed testing is an integral part of a responsible development process. However, it is important to note that it is never too late to conduct tests — even if your product has been operating for many years.

During testing, QA most often plays the role of a hacker and begins to manipulate the application or website in various ways:

• Tries to find out the password using external ways.
• Attacks the system using special utilities that analyze the level of protection.
• Inserts errors and tries to penetrate the system during recovery.
• Views non-secret and non-hided data in the hope of finding the key to enter the system.

To emphasize the importance of testing, consider these:

Cybersecurity Ventures experts estimated that by the end of 2023, global cybercrime caused losses of $8 trillion. Furthermore, the volume of losses could exceed $10 trillion in 2024–2025.

• The IoT Testing

Asthe Internet of Things (IoT) expands, new testing strategies are necessary. IoT systems are composed of many devices that can interact with each other. Testing such systems needs to take into account the diversity of devices, networks, and usage scenarios. This requires the development of unique test environments and the use of automation to test many different combinations.

The main concept of IoT is the ability to connect all kinds of Things that a person can use in everyday life, such as, a refrigerator, air conditioner, car, bicycle, and even sneakers. All these Things must be equipped with built-in sensors that collect environmental information, exchange data, and perform various actions based on the received information. An example of this concept in action is the “smart house” system. This system analyzes environmental data and adjusts the room’s temperature accordingly. In winter, it regulates heating intensity, while in hot weather, mechanisms automatically open and close windows to ventilate . All of this happens without human intervention.

Before joining Growe, I worked in this area for almost 3 years. The company’s focus was on developing devices and software for Bluetooth or UWB tracking. One of the most notable projects I worked on as QA was a solution designed for mines.Our development was integrated into a miner’s lamp. This “tag”, through the exchange of Bluetooth packets with beacons placed every 10 meters in the mine, sent data to the backend to determine approximate coordinates. After applying complex algorithms, the miner’s location inside the mine was displayed on an interactive map on the dashboard. Additionally, the smart lamp could measure the levels of dangerous gases in the mine and, at the push of a button, send an SOS signal directly to the operator on the dashboard.

As you can imagine, both development and testing in this area are highly complex and carry a great deal of responsibility.

• Transition from Manual to Automatic Testing

Testers are switching from purely manual tasks to more technical ones, such as developing automated test scenarios. This shift increases the importance of testers in the development team. To master automation, QA should know the basics of programming, understand the principles of working with various automation tools, and know the basics of DevOps to integrate their tests into CI/CD processes.

Focus on Business

The business-oriented tester is becoming an increasingly valuable participant in the product development process. They don’t just check for features and bugs but also help ensure the product’s success in the market by focusing on the business and end-user needs. This expands their role in the team and increases their influence on the final result, making testers an integral part of the business strategy.

Considering the widespread implementation and hype around AI & ML, this will be one of the main directions for the upcoming years.

Must-have Skills for Future QAs

QAs need to constantly upgrade their hard skills, adapt to new trends, and develop their understanding of business processes. The integration of AI, the increasing focus on cybersecurity, the development of IoT and automation, as well as business focus — all these aspects change the standards for testers. Below are several skills that are worth developing:

• AI/ML basics

Understanding AI and ML principles is essential for leveraging these technologies to automate testing, analyze results, and detect bugs effectively.

It is important to highlight that a wide range of AI/ML-based tools are available and worth exploring for your products and processes. These tools can help with automated test generation, intelligent defect detection, and full testing coverage, increasing testing efficiency and product quality.

Some of these tools include:

• Testcraft. A free and open-source browser extension for software testing. It simplifies the process of generating test cases for any screen.
• Selenium. A versatile testing tool equipped with AI capabilities, offering flexible and efficient test execution.
• Functionize. Provides end-to-end, self-healing, and cloud-scalable tests, enabling faster development and improved quality.

• The automation skills

Deep knowledge of programming languages such as Python, Java, and JavaScript is crucial for writing scripts. Additionally, expertise in test automation tools like Selenium, Cypress, Appium, and JUnit is needed, along with their integration into CI/CD pipelines.

It’s also important to emphasize the role of DevOps — understanding DevOps processes and integrating automated tests into CI/CD processes using tools such as Jenkins and GitLab CI.

• Knowledge of cybersecurity

Knowing the principles and practices of cybersecurity will be significant, considering the growing focus on data and system protection.

Success in penetration testing and cybersecurity requires a blend of technical and analytical skills. Key skills include a deep understanding of networks, operating systems, and protocols. Proficiency in programming languages like Python or JavaScript is crucial for developing custom scripts and tools. Knowledge of ethical hacking techniques and familiarity with security tools such as Nmap, Metasploit, and Wireshark are essential. Additionally, strong problem-solving abilities, attention to detail, and the ability to stay updated with evolving threats are vital for success.

• Business analysis and risk management

Understanding the business background and the impact of quality on the organisation’s overall success will help you better respond to business requirements and ensure the effective integration of QA into business processes.

These skills will help QA professionals to adapt to industry changes and maintain their relevance in the face of technological change. With continued development and improvement, QA engineers can effectively respond to new challenges and maintain high software quality.

P. S. In conclusion, I would like to emphasize once again that I absolutely love the work I do. And I truly believe in the development and success of the QA profession in any of its forms.