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Revolutionising Quality Assurance: AI Automation Drives Digital Acceleration in Software Testing

Low-Code/No-Code Innovations and AI-Powered Automation Transforming the Landscape of Software Development.


In the rapidly evolving landscape of software development, the role of a 'quality champion' now demands more than just technical prowess. Embracing the right mindset and leveraging innovative quality engineering tools have become imperative for businesses aiming to stand out in the competitive digital realm.


Low-Code/No-Code Test Automation:


The surge in low-code/no-code technology is reshaping the way organisations approach automation, allowing individuals beyond the development team to enhance the quality of app engineering and delivery processes. Enabling testers, business analysts, and executives to automate routine workflows, this approach is forecasted to drive a nearly 20% growth in the global low-code development technologies market, reaching a substantial $27 billion by the year-end, as per Gartner.


Modular low-code/no-code frameworks empower teams to tailor workflows to specific business needs without compromising quality. By reducing IT backlog and streamlining development processes, DevOps teams can operate more efficiently, maintaining high-quality software and extracting greater value from technology investments.


Moreover, extending this efficiency to low-code/no-code automated testing solutions significantly reduces time spent on verifying platform updates. This streamlined approach enables DevOps teams to navigate ever-changing workflows while ensuring sustained software quality.


AI-Powered Automation:


According to the World Quality Report, 86% of CIOs and senior tech leaders consider artificial intelligence (AI) a crucial factor in selecting quality assurance (QA) solutions. Despite ongoing debates surrounding AI adoption, successful enterprises are those adept at harnessing available tools for digital acceleration.


Research and advisory firm Forrester identifies key areas where AI-powered automation transforms software testing:


- Test Design and Optimisation: AI aids in reviewing, assessing, and increasing coverage, enhancing productivity and enabling faster innovation.


- Visual Testing: Unlike traditional automated tools, visual testing allows applications to be assessed as humans see them, identifying issues related to unexpected rendering discrepancies.


- Intelligent Bug Hunting: AI assists in identifying common failure patterns and prioritising tests with the most bugs, although human intervention remains crucial for a comprehensive review.


Quality Engineering Communities:


In addition to innovative tools, access to knowledge and communities plays a pivotal role in fostering a quality champion's success. Online communities dedicated to quality management and engineering serve as vital platforms for collaboration and knowledge-sharing among professionals.


These resources facilitate an engaging learning space for quality professionals, developers, testers, executives, and industry leaders. They play a crucial role in driving best practices, encouraging continuous learning, and fostering a culture of improvement in a collaborative environment.


As the digital landscape continues to evolve, businesses that embrace low-code/no-code innovations and harness the power of AI automation are positioned not only to meet the challenges of accelerated software development but also to lead the way in quality-driven innovation.


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