As the tech sector faces unprecedented upheaval and widespread layoffs, the QA industry is feeling the impact, grappling with new uncertainties and the rise of automation and new technologies, most prominently AI.
This shifting landscape presents significant challenges that demand attention.
In fact, it’s time to confront how these changes are reshaping the world of quality assurance and what it means for professionals in the field.
At least that is the message from Ruslan Desyatnikov, founder and chief executive officer of QA Mentor, a software testing company headquartered in New York City.
He recalled that, from 2022 to 2023, major tech firms carried out significant job layoffs. Amazon let go of 27,000 workers, Meta dismissed 21,000 and Microsoft laid off 10,000.
“These figures have only grown as we moved into 2024, as over 500 tech companies have made job cuts, resulting in over 100,000 employees losing their jobs since the start of this year,” Desyatnikov said.
“This is a world away from 2020-2021,” he continued, “when the Covid-19 pandemic accelerated the digital transformation that led to heightened demand for tech products and services, such as remote work tools, e-commerce platforms and digital entertainment.”
During this period, tech companies saw stock prices soar on investor optimism in a pandemic-changed world.
Global central banks kept interest rates low to aid economic recovery, allowing tech firms affordable borrowing for growth, Desyatnikov stressed, pointing out that government stimulus and aid bolstered businesses, including tech, amid pandemic uncertainties.
“As the global economy faced renewed challenges around 2022, including rising inflation and interest rates, tech giants shifted gears from their aggressive hiring stance of 2020-2021,” Desyatnikov wrote in recent Forbes analysis.
“Now, they’re cutting back on hiring and implementing layoffs to ensure financial stability post-pandemic. This abrupt change is reshaping employees’ career trajectories from optimism to uncertainty almost overnight,” he stated.
Enhancing QA
Amid this industry upheaval, Desyatnikov is convinced the QA sector must seize the opportunity to leverage automation and AI to stay competitive.
“As AI testing solutions advance, QA professionals need AI tools to remain marketable,” he stressed.
By integrating AI, companies can optimize efficiency with AI. “AI-driven tools quickly spot patterns and anomalies often missed by traditional methods, streamlining testing, cutting manual work and boosting productivity,”
Desyatnikov said, adding that AI also prioritises test cases based on data, ensuring focus on critical areas.
Moreover, AI reduces manual labour by predicting defects early, minimising rework and errors. “AI-driven resource management enhances efficiency and keeps budgets lean,” he said.
“To effectively address the challenges facing the QA industry, firms must adopt an approach that includes targeted employee training and upskilling.”
– Ruslan Desyatnikov
Further, he calls on the industry to enhance human resource allocation.
“With routine tasks automated, QA teams can tackle complex challenges and innovation. AI augments human expertise, allowing teams to focus on strategic initiatives and elevate service delivery,” Desyatnikov explained.
In addition, the QA space should develop new AI-driven services.
“Adopting AI enables companies to create new testing services tailored to evolving market needs. AI offers the scalability and adaptability needed to stay ahead with innovative solutions,” he said.
Also, Desyatnikov thinks it’s vital workflows are modernised. “AI accelerates test execution by auto-generating cases and scripts, improving accuracy and ensuring consistent, reliable results across environments,” he noted.
Finally, firms should strengthen risk management. “AI-powered testing tools help identify potential risks early in the process, offering predictive insights that reduce the likelihood of critical failures,” Desyatnikov shared.
“This proactive approach helps ensure higher-quality releases and mitigates costly issues in production,” he added.
QA team capabilities
Addressing these challenges may not be an easy task, Desyatnikov warned, as he believes the QA space still has a long way to go.
“To effectively address the challenges facing the QA industry, firms must adopt an approach that includes targeted employee training and upskilling,” he said.
To enhance QA teams’ capabilities, it is vital to implement continuous learning programs, by focusing on advanced testing frameworks such as Selenium, Appium and JUnit to ensure QA engineers are proficient in the latest tools and methodologies.
Also not unimportant, Desyatnikov argues that companies should provide training in areas like API testing, security testing and performance testing using tools like Postman, OWASP ZAP and Apache JMeter.
This all should lead to a culture in which expertise in test automation scripts is fostered, he stressed. “Encourage the use of languages like Python, Java and JavaScript to keep teams agile and adept at handling evolving testing requirements.”
Also a step that should not be skipped, Desyatnikov argues, is to invest in employee development. “Provide access to industry conferences and webinars to keep teams updated on the latest trends and best practices in QA.”
Data-driven insights
In the context of present challenges, sticking to traditional methods is no longer sufficient, Desyatnikov continued.
“To stay competitive, companies must integrate data-driven insights into their quality assurance strategies,” he said.
“Begin by utilizing analytics tools to thoroughly analyse test results, track performance metrics and uncover patterns,” Desyatnikov added.
He believes this approach provides a clearer picture of where to direct testing efforts and how to refine processes.
“Adopting AI enables companies to create new testing services tailored to evolving market needs.”
– Ruslan Desyatnikov
Desyatnikov also thinks predictive analytics can help teams anticipate potential issues before they become critical, reducing the risk of defects in production.
“Optimising resource allocation becomes more precise with data,” he explained.
“By understanding workload and performance metrics, you can ensure that high-priority tasks receive the necessary focus and attention. Data insights also help refine test coverage strategies, revealing gaps and overlaps to ensure comprehensive and targeted testing.”
In other words, cultivating a data-driven culture is essential, he stressed, namely to “equip QA teams with the skills and tools to interpret data effectively, promoting a proactive approach to quality assurance and driving excellence in your testing processes.”
In summary, Desyatnikov said that, by optimising efficiency, controlling costs, modernizing workflows and upskilling employees, QA professionals can turn disruption into innovation.
“It’s time for the industry to shed its old skin, rise above the chaos and redefine what quality assurance means in a post-pandemic world,” he said.
“The future belongs to those who can navigate the turbulence with agility and foresight,” Desyatnikov concluded.
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