Artificial intelligence is poised to revolutionize industries, but concerns about its limitations in business and digital testing persist among users.
While customer experience (CX) and quality assurance (QA) differ significantly, the risks associated with AI’s involvement extend beyond just user satisfaction. Critics continue to argue that AI-driven CX systems often yield unsatisfactory results and threaten to displace human workers.
Similarly, AI-powered digital testing tools face scrutiny over their accuracy and the potential to replace human testers. Gartner predicts that by 2027, 80% of businesses will incorporate AI-augmented testing tools into their software engineering workflows. Additionally, the software testing market is expected to grow at a compound annual growth rate (CAGR) of 5% from 2023 to 2027.
This growth has fueled fears that AI could supplant software testers, with the potential for testing failures disrupting the software supply chain.
However, Tal Barmeir, co-founder of AI-based testing company BlinqIO, believes this is unlikely. Instead, she envisions AI transforming the role of human testers into “AI-assisted testers,” where AI serves to enhance their productivity and effectiveness. Barmeir argues that the fear of AI replacing testers ignores its potential for collaboration, which can elevate their performance rather than diminish it.
“While AI adoption in software testing is on the rise, it’s unlikely to fully replace human testers. AI tools excel at handling repetitive, data-heavy tasks, allowing human testers to focus on more complex scenarios that demand critical thinking and decision-making,” Barmeir told TechNewsWorld.
Addressing AI Anxiety with Multichannel Approaches
Improving the skills of human workers in call centers, sales, and testing environments can yield similar benefits. Barmeir suggests that training traditional testers to leverage AI tools can significantly boost productivity and efficiency.
“By incorporating AI tools, testers can automate routine aspects of testing, enabling them to conduct more tests in less time with greater accuracy. This shift not only accelerates the development process but also frees testers to focus on areas requiring more insight, such as user experience and security,” she explained.
Barmeir makes a compelling case for how AI can enhance software testing and improve business outcomes.
“Humans will remain essential in software testing due to their ability to understand context, interpret complex user behaviors, and make ethical judgments. While AI excels at analyzing data and identifying patterns, it lacks the capability to comprehend context or make decisions based on values, areas where human judgment is critical,” she said.
Furthermore, advancements like the AI Test Recorder, which automates the capture and reproduction of test scenarios, are improving AI testing capabilities. Still, human oversight remains essential.
“Humans are crucial in monitoring and interpreting results, ensuring tests adhere to ethical standards and business objectives, and providing the contextual understanding that AI cannot yet replicate,” she concluded.
Isolated Use Cases, Shared Human Roles
Does this reasoning apply to AI replacing human workers in other areas? According to Barmeir, AI’s influence on employment varies by sector. In industries like manufacturing or data entry, AI may take over repetitive tasks that were once handled by humans.
“However, in fields that require interpersonal skills, creativity, or complex decision-making, AI is more likely to complement human abilities than replace them. The key is to use AI as a tool that enhances and supports human expertise,” she explained.
Barmeir emphasized that companies must adjust their often misguided views about AI, particularly regarding its use in customer experience. To address the growing concerns about AI in customer interactions, businesses should focus on transparency, personalization, and control.
“This involves clearly communicating how AI is utilized, ensuring that interactions are as personalized and empathetic as those with humans, and providing users with the option to choose between AI-assisted and human services,” she said.
The State of Software Testing
Barmeir believes the software testing industry is undergoing a major transformation, driven by AI and machine learning technologies. Two key trends are shaping this change.
First, there’s a strong emphasis on automating routine testing procedures to increase efficiency. Second, maintaining a solid framework for security and performance testing remains essential.
“This shift towards automation is significantly reducing the time to market (TTM) for new software releases, which is a critical advantage in today’s fast-moving digital world,” she asserted.
By enabling quicker deployment cycles, businesses can respond faster to market demands and act on feedback more effectively. This approach not only enhances the development process but also helps companies stay competitive in the digital economy.
Pros, Cons, and the Future for AI-Assisted Testers
Automation greatly speeds up the testing process and minimizes human error. It allows testers to focus on more intricate aspects of the software, improving both efficiency and accuracy.
AI also outperforms manual testing by handling larger workloads and more complex scenarios with greater effectiveness. This capability makes it easier to scale testing efforts as software grows in complexity and business demands evolve.
However, there are drawbacks. For example, certain issues might be overlooked, and there’s a need for continuous updates to align with new software changes. Barmeir cautioned that this could require significant ongoing investment in time and resources.
The future for AI-assisted testers looks promising, with opportunities to democratize the field and make it more accessible to entry-level participants. AI tools reduce the barriers to entry, allowing individuals with less technical expertise to engage in testing processes.
“This democratization means more people can contribute to software testing, expanding the talent pool and encouraging innovation,” she concluded.
Reshaping the QA Industry
Barmeir emphasized that AI is transforming the QA industry by automating repetitive tasks and introducing advanced tools such as the AI Test Recorder and Playwright. These tools work in tandem to speed up the testing process while maintaining high standards of quality and reliability in software products.
The AI Test Recorder captures a test requirement and efficiently generates a comprehensive test suite in Playwright. The platform’s code feature further streamlines automation by enabling users to create test scripts through recorded interactions with a website, eliminating the need for manual coding.
