{"id":18359,"date":"2022-12-01T19:32:17","date_gmt":"2022-12-01T14:02:17","guid":{"rendered":"https:\/\/cigniti.com\/blog\/?p=18359"},"modified":"2022-12-01T19:33:08","modified_gmt":"2022-12-01T14:03:08","slug":"scriptless-test-automation-tool-resource-skill-gap","status":"publish","type":"post","link":"https:\/\/www.cigniti.com\/blog\/scriptless-test-automation-tool-resource-skill-gap\/","title":{"rendered":"How AI-Powered Test Automation Tools Can Address the Talent Shortage"},"content":{"rendered":"

Digital aspirations for global organizations are driving innovation-led initiatives. As Agility and Flexibility within the development life cycle become the norm, it is essential to re-emphasize the need for not just delivering fast, but also delivering quality and value at speed.<\/p>\n

By putting customers at the center of the value chain, organizations are aiming to streamline their value delivery systems. However, they are struggling with the most important component to facilitate this \u2013 human resource.<\/p>\n

According to a McKinsey survey<\/a> of more than 1,500 senior executives globally, some 87% say their companies are not adequately prepared to address the skill gap. Evidently, talent shortage is a serious issue that the global IT sector is facing.<\/p>\n

With the rapid technological advancements, it is humanly impossible to be abreast with all the new developments. Upskilling and reskilling also have their limitations. This is where, a harmonious marriage is necessary between technology and human resources. Let\u2019s discuss how technology, while resulting in these challenges, can also be a solution.<\/p>\n

The rise of AI-augmented software testing tools<\/strong><\/p>\n

\u201cBy 2027, 80% of enterprises will have integrated artificial intelligence (AI)-augmented testing tools into their software engineering toolchain, which is a significant increase from 10% in 2022\u201d, predicts Gartner.<\/p>\n

As per the Gartner Market Definition<\/a>, AI-augmented, software-testing tools provide capabilities for advanced, self-optimizing and adaptive automated testing through the use of AI technologies, such as machine learning (ML), self-healing heuristics or computer vision. AI-augmented testing tools streamline, accelerate, and improve the test workflow, as models can be retrained based on the data collected from the activities they perform \u2014 thereby enhancing human productivity.<\/p>\n

Test automation skillset gap in software testing<\/strong><\/p>\n

Manual testers bring domain expertise, business acumen, and emotional quotient to the overall testing process. At the same time, automation is imperative to accelerate software testing and align it with the overarching delivery timelines. While automation offers the promise of faster testing, implementing successful software test automation is another story.<\/p>\n

In a Gartner survey<\/a>, IT executives cited talent availability as the main adoption risk factor for the majority of\u202fIT automation\u202ftechnologies (75%) and nearly half of the digital workplace technologies (41%).<\/p>\n

The pace at which applications evolve requires constant maintenance and upgrade of automation scripts. Manual testing is not feasible in such cases. Neither are there enough skilled resources, nor sufficient time to dedicate to getting the desired coverage. Especially, scripting-based test automation tools require programming skills that are rarely available at scale.<\/p>\n

Democratizing test automation to bridge the skill gap<\/strong><\/p>\n

Gartner predicts that, by 2025, 70% of new applications will be developed with low-code\/no-code technologies. These technologies help to eliminate manual processes and enable citizen developers to build applications, which increases employee engagement and productivity.<\/p>\n

Democratization or leveraging \u2018Citizen Developers\u2019 using low-code\/no-code scriptless tools<\/a> can bring down the barriers to test automation by promoting collaboration across multiple personas of technical testers, dev testers, and business testers. AI-infused technologies coupled with multi-persona expertise will result in production-grade test automation suites and an accelerated test automation cycle<\/a>.<\/p>\n

\"Democratizing<\/strong><\/p>\n

Becoming deployment ready with iNSta<\/strong><\/p>\n

iNSta is designed to eliminate the barriers to test automation, which commonly are:<\/p>\n