Enterprises must deliver agile projects with high quality, velocity, and reduced efforts, which is one of the critical challenges that induces increased automation. However, realizing where to apply automation is essential for successful transformation.
Before choosing a new set of tools, it is crucial to have a well-strategized testing process. Evaluate the existing testing process maturity and the potential optimization areas for an automated testing solution. Analyze and understand the demands of your team and organizational goals.
Application leaders must understand:
The demand for software testing tools is rapidly increasing from managing simple test execution to applying AI through the entire testing phase. AI-powered test automation tools such as IntelliSWAUT provide capabilities for advanced, self-optimizing, and adaptive automated testing in the following areas.
By 2022, 40% of application development (AD) projects will use AI-enabled test set optimizers that build, maintain, run and optimize test assets.
IA technologies, along with self-healing scriptless test automation tools, apply AI and ML to actively adapt testing to make modifications in an application’s user interface (UI) or platforms. To identify existing objects, it scans the entire application UI after the execution of tests. Further, they match them to the previous application model for the automated tests.
Scriptless test automation enables organizations to manage the increased density of data.
AI-powered tools identify bugs, help diagnose the occurrences, and make efficient decisions. Also, integration of any technology stack can be possible with AI-driven tools.
AI enables a more significant focus on innovation and enhanced accuracy of self-healing automation.
DevOps enables seamless collaboration between developers, testers, clients, and end-users to deliver consistent business value.
Create related virtual groups aligned around a general business purpose to focus more on innovation and fetch a variety of ideas from everyone.
The revolution in the automation testing market has advanced well to power up the enterprises in their digital transformation journey with their AI-enabled cutting-edge technologies.
The use cases of AI/ ML/RPA makes Testing, Data management, Performance, Security, Compliance, Plaform management, and virtualization process more advanced and help embrace digital technologies without interruptions. Industry leaders can use their automation capabilities at the outset of an engagement to evaluate ROI and the impact on the business processes where the ML-powered test automation tool is a best fit. Most business leaders are already familiar with RPA and aware of the advantages RPA brings from a business process efficiency standpoint. However, the focus of tech CEOs needs to be on how ML can be considered for testing, mainly where business users are not technically savvy.
Due to the covid-19 crisis, the remote working culture and the increasing demands for improved customer experiences have increased the need for intelligent automation. Organizations continue to stay up-to-date to a continuous testing environment to embrace automation across the organization.
Many companies started to invest in AI and IA technologies to optimize test automation and improve production quality.
Business leaders must understand:
Where to apply Intelligent Automation in each phase of application testing?
What use cases to focus on?
What criteria to use?
Sun Technologies can help you automate your business by incorporating AI/ML technologies into your projects and business environments. Our test automation offerings are flexible so, you can ask for any particular service depending on your requirements. Our higher level of test reliability with improved accuracy boosts efficiency by transforming DevOps with the benefits of AI Ops and QA Ops. Contact our solutions expert today and get answers to all your queries.
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