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AI in Quality Assurance: Transforming the Testing Landscape

AI in Quality Assurance: Transforming the Testing Landscape

The hype of Artificial intelligence (AI) is real, and here to stay. Its impact has been felt in many industries and specializations, including quality assurance (QA). AI is now reshaping the way testing processes are conducted and optimizing efficiency in unprecedented ways. But what exactly is AI in quality assurance? As QA professionals navigate these new developments, understanding the profound impact of AI on testing roles and methodologies becomes imperative.

This article explores the impact of AI in QA, applications, benefits, and implications for the future of ecommerce testing. So without further ado, let’s get started.


How is AI used in Quality Assurance

Let’s first look at how AI is used in quality assurance. While test automation has helped organizations overcome the limitation of traditional testing approaches, AI is now revolutionizing the way we do quality assurance. By harnessing technologies such as natural language processing (NLP), machine learning (ML), and advanced visual data analysis, AI is paving the way for more agile, scalable, and accurate testing.

Test Creation and Management

One of the key use cases of AI in QA is its ability to facilitate effortless test creation and management. AI-powered solutions enable QA teams to create tests based on user behavior. For example, such tools can analyze user data to determine the most popular ecommerce journeys, and reprioritize test flows accordingly. 

In addition, the introduction of NLP and Generative AI removes coding barriers, enabling testers to provide natural language instructions that translate into executable test scripts. Such testing tools are not only more accessible to non-technical users, but also offer flexibility and customization options that are lacking in many of the current no-code test automation tools.

Resolving the Limitations of Manual Testing

While manual testing has its purpose and place in quality assurance, it cannot escape the inefficiencies and inaccuracies inherent in human-driven processes. However, with the advent of AI in QA, test teams can address these limitations. QA teams are leveraging AI-driven tools to manage repetitive tasks, defect detection, and analysis, driving more robust and reliable testing outcomes in ecommerce quality assurance. 

AI in Exploratory Testing

Related to manual testing, the use case of AI in exploratory testing has also shown plenty of promise. Exploratory testing benefits greatly from creativity, and Generative AI serves as a valuable resource.. Thanks to its extensive pre-training on vast datasets, tools such as ChatGPT offer an excellent means to brainstorm fresh testing ideas.

Here’s a simple prompt example to illustrate the above:

Given the following user story, can you enumerate some exploratory test ideas? Please include test steps.
As a customer, I want to add products to the cart so that I can checkout.

ChatGPT Prompt Example for Exploratory Testing

However, caution needs to be exercised when it comes to the use of Generative AI for this purpose. ChatGPT, while possessing impressive capabilities, is often unable to grasp the entire context to the same extent as human testers. It may lack a deep understanding of an ecommerce’s purpose, user journeys, and its target audience, making its use potentially time-consuming (contrary to its intended ease).

Benefits of AI in Quality Assurance

We have explained the main applications of AI in Quality Assurance. Whether in improving tools, processes, analysis, etc., we can already see how the use of AI in QA offers a myriad of benefits:

Greater Efficiency and Speed

AI can perform tests faster and more frequently than human testers, leading to the detection of issues earlier in the development cycle. This improvement in testing efficiency and speed enables organizations to optimize resource utilization and accelerates time-to-market.

Cost-savings and Increased ROI

By reducing manual effort and the risk of human errors, AI helps ecommerce businesses save costs associated with testing. Additionally, AI-driven QA enhances ROI by improving product quality and reducing defect resolution time.

Increased Test Coverage and Scalability

AI enables QA teams to handle large volumes of test cases and achieve comprehensive test coverage. With AI-powered test automation, QA teams can act faster to scale their testing efforts, to meet the demands of evolving business requirements.

Intelligent Issue Analysis and Classification

Another potential benefit of AI is intelligent testing that can quickly distinguish between expected changes and actual errors. Taking an example of a dynamic ecommerce site which regularly implements new site features, catalog updates, marketing changes, etc. AI can correctly identify genuine UX issues from such changes.

Using AI for intelligent identification and classification of issues not only reduces the likelihood of false alarms or false positives detected, but optimizes testing resources.

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The Future of AI in Quality Assurance

AI in Quality Assurance enables professionals in the field to concentrate on critical thinking, exploratory testing, and strategic decision-making, instead of repetitive manual tasks. Nevertheless when we talk about the future of AI in Quality Assurance, it is in fact close to, or already a reality.

Let’s frame the future of AI in Quality Assurance by addressing common questions asked by QA professionals regarding its impact:

Can QA be replaced by AI?

While AI can perform many QA tasks, it cannot replace human testers entirely. For one, human testers bring a level of creativity and critical thinking that AI cannot replicate. However, AI can significantly reduce the need for manual testing, freeing up human testers to focus on more complex tasks.

There is the promise of Autonomous Testing – tests can be completely created, managed, and executed through AI technologies, without the need for human intervention. Nevertheless, there is still a lot of work to be done in this field.

What does AI mean for QA testers? How will AI impact the roles of QA? 

Not too long ago in ecommerce development life cycles, errors are fixed after they have been made. Now, ChatGPT and other AI tools can proactively analyze code during development and make adjustments before errors even occur. Nevertheless, QA roles (whether SDETs, Quality Engineers, or QA leads) will still remain in order to maintain high-quality even as development moves faster. 

What is important to note is that the role of a QA tester looks to be potentially shifting to develop new skills. The focus of QA professionals is now on more complex tasks such as AI training and harnessing its power to drive more efficient testing. This in turn will expand their skill sets and capabilities outside of the current boundaries of QA. 

How will AI change current testing methodologies and best practices?

While AI is set to significantly change testing procedures and best practices, the fundamentals of Quality Assurance will largely remain intact. Certainly through rapid testing and the automation of repetitive tasks, AI can help further drive the iterative testing process throughout the entire ecommerce development process.

AI can also analyze vast amounts of data in real-time, enabling businesses to make informed decisions based on trends, patterns, and insights, leading to a more proactive approach to quality management.

Leverage The Power of AI with Valido App

AI represents an important shift in how we perform quality assurance in ecommerce. It offers unique opportunities for organizations to drive more efficient, intelligent, and effective testing processes. By embracing AI and understanding how it benefits QA, organizations can achieve superior testing outcomes, drive greater ROI, and stay ahead of the competition.

At the forefront of AI-powered QA solutions lies Valido App, a cutting-edge platform designed to optimize testing and monitoring processes in ecommerce. Leveraging the power of generative AI and intelligent tests, Valido App empowers businesses to identify and resolve web performance and UX issues with speed and accuracy.

Valido App uses Generative AI to quickly formulate personalized recommendations for detected issues. This enables ecommerce businesses to resolve issues faster and more effectively. Valido App also automatically generates tests for your ecommerce with a single click, based on predictions of user sessions.

By using Valido App, businesses can take advantage of the power of AI to improve their QA processes, leading to increased test efficiency, accuracy, and cost savings.

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