5 ways that artificial intelligence can help with QA

Artificial intelligence is undeniably the technology of the day, with applications ranging from a basic social media filter that alters a person's voice or image to being integrated into workflows as critical as quality assurance.

When reviewing a component of a software product, for example, quality control is a critical process that requires adequate attention to detail, which can cause errors when done by a human. This is why artificial intelligence technologies began to be implemented to strengthen this flow and reduce the list of errors to the bare minimum possible.

What exactly is quality assurance (QA)?

A software project requires numerous processes to be completed effectively, one of which is quality assurance, or QA, because the person or team in charge of this has the duty of validating all of the components and ensuring that each one works as it should.

This task can be done manually or automatically, with a variety of instruments available on the market. One of the most modern quality assurance processes incorporates artificial intelligence into its workflow.

How artificial intelligence may help with quality control

There are artificial intelligence-powered technologies that can considerably improve the work process of the team in charge of checking each step and component developed in a software project.

These are the five areas of quality control where an artificial intelligence technology can help:

Manual testing chores should be automated

Repetitive testing procedures, like as regression testing, can be automated by AI, freeing up tester time to focus on more complicated cases. It can also automate cross-browser testing.

Expand test coverage

Using an AI-powered tool, test cases covering a greater range of scenarios may be developed and executed, enhancing test coverage and decreasing the probability of faults being discovered.

Enhance flaw detection

One of the primary goals of the quality assurance process is to ensure that the code and the software product as a whole are defect-free. Artificial intelligence can evaluate enormous amounts of data to detect patterns and anomalies that human evaluators may miss.

Predictive modeling

The QA team benefits greatly from staying ahead of the curve, which they can achieve with artificial intelligence. They can evaluate previous data using a tool enabled by this technology to identify potential flaws or risk regions, allowing testers to focus on those areas.

Improve efficiency

Artificial intelligence can assess test findings and identify areas where testing might be simplified or streamlined, lowering testing costs and time.

Overall, AI can help improve quality control by lowering testing time and expense, boosting testing coverage and efficiency, and improving fault detection and prevention accuracy and efficacy.

Other industrial applications of artificial intelligence

Many businesses are beginning to embrace artificial intelligence (AI) for a variety of reasons. These are some of the most common applications of artificial intelligence in today's industries:

• Healthcare: Artificial intelligence (AI) may be used to evaluate massive volumes of patient data and aid clinicians in diagnosis and treatment planning. It's also useful for remote patient monitoring and drug development.
• Finance: Artificial intelligence can be used to detect fraud and improve risk management. It can also offer tailored investing advice and optimize portfolios.
• Retail: AI can be utilized to improve customer service through chatbots and virtual assistants. It can also be used to improve inventory management and personalize shopping experiences.
• Transportation: AI can be utilized to improve the safety and efficiency of driverless vehicles. It can also be used to optimize logistics and supply chains.
• Manufacturing: Artificial intelligence (AI) can be utilized to improve quality control and predictive maintenance. It can also improve production operations and decrease downtime.
• Education: Artificial intelligence can be utilized to customize students' learning experiences. It can also be used for grading and evaluation, as well as determining the success of educational approaches.

Artificial intelligence continues to gain traction as a technology favored by businesses globally. Rootstack has collaborated with her on various projects and can assist him in bringing his concept to life.

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