- AI
- QA
Quality assurance will remain relevant with AI
December 8 - 23
In this era of rapid technological changes, the rise of automation and artificial intelligence (AI) has disrupted traditional processes across industries. The field of quality assurance (QA) is no exception, as organizations increasingly embrace AI-powered testing tools and automation to streamline their software development lifecycles. However, manual QA professionals must adapt and evolve to remain relevant in this changing landscape.
The evolving QA landscape
Manual QA has been the backbone of software testing for decades, ensuring the quality and functionality of applications before they are released. Automated testing has been widely adopted at the unit, functional, and often at the integration levels, but there is still a layer humans have to perform since it’s typically too costly to automate. However, AI is reshaping the QA landscape by providing faster and more efficient ways to test software. AI algorithms can identify patterns, analyze large datasets, and even perform complex tasks like image recognition, ultimately enhancing testing accuracy. As a result, manual testing, which depends heavily on human intervention, is facing increased pressure to demonstrate its continued value.
AI won’t replace manual testing
While the rise of automation and AI may raise concerns about the future of manual QA, it is crucial to recognize that these emerging technologies are not intended to completely replace manual testers. They are meant to enhance and augment existing QA processes. Manual QA still plays a critical role in certain areas that require human intuition, creativity, and adaptability. Manual testers are best suited for exploratory testing, usability testing, and identifying edge cases that automated tools may miss. Making sure the app feels intuitive, focusing on the “wow” factor, and bringing the perspective of the end-user are all things that only a human can and should judge.
Preparing for the future of AI in QA
Mirego recommends the following strategies to manual QA profesionals seeking to continue providing value in a world increasingly influenced by automation and AI:
Specialize in niche areas
Identify and focus on specific areas where manual testing skills are still highly valued. For instance, accessibility testing and user-centred testing rely heavily on manual intervention due to their complex nature. Becoming an expert in these specialized areas can make you an invaluable asset to your organization.
Develop soft skills
While technical proficiency is essential, developing soft skills can significantly enhance your value as a manual QA professional. Effective communication, collaboration, and problem-solving skills are vital in bridging the gap between end-users and developers. Additionally, being adaptable, proactive, and open-minded will help you navigate the changing landscape and embrace new technologies more effectively.
Get trained and perfect your skills
Training QA professionals to understand and implement AI-driven testing strategies is crucial for enhancing testing efficiency and accuracy. It is essential to discern when the use of AI is valuable and to effectively manage its sometimes biased responses. While AI can easily generate generic testing scenarios, handling more complex features requires additional context and time to ensure that tasks are executed as desired. In such scenarios, devising the test strategy independently may prove more time-efficient than relying on AI.
Think about safety first!
It is imperative that we prioritize the safe and ethical use of AI. This includes taking precautionary measures to protect data privacy and intellectual property. We must never share confidential or proprietary data with AI systems without appropriate safeguards. Anonymizing sensitive data before sharing it with AI tools is paramount, especially while using public AI tools like ChatGPT.
Focus on collaboration and integration
As is often seen in the current software development landscape, there is a growing emphasis on integrating AI-driven quality assurance into various stages of the software development lifecycle. This integration is not just a technological shift, but a paradigm shift aimed at ensuring quality throughout the process. By harnessing the potential of AI in QA, manual testers can enhance their contribution to software quality. We believe that adapting to this changing landscape will shape the future of QA in a way that benefits both organizations and end-users alike.
From tester to quality advocate
The future of QA isn't just about finding bugs; it’s about advocating for quality every day, empowering teams to build better products the first time. By harnessing the power of AI tools, we can proactively mitigate potential threats before they manifest in code, avoiding costly rework. AI tools can play a pivotal role in enabling QA professionals to provide swift feedback on newly developed features, effectively reducing the testing gap between feature implementations. They also help improve test coverage by recommending scenarios that were initially overlooked or missed, resulting in a superior quality product. The goal is not merely to detect bugs but to prevent them altogether.
As automation and AI reshape the QA landscape, QA professionals must adapt. While these technologies enable faster testing, manual testers still add value through human intuition and creativity. To thrive, they must specialize in niche areas, develop soft skills, and embrace the role of quality advocate. By harnessing AI tools, manual testers can proactively prevent bugs and provide feedback faster than ever, resulting in outstanding quality products.