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AI is the future of test automation- Are you Ready?

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Traditional QE Isn’t Working Anymore

Traditional tried-and-tested methods of testing and quality need to catch up in today’s changing environment.

A siloed approach: Typical QE teams are separated from development teams. This structure concentrates on optimizing the subcomponents and deviates from the true purpose of enhancing the user experience.

Slowing overall engineering velocity: Traditional quality engineering has been chiefly manual, impeding rapid development and operations procedures.

Expensive: Traditional QE requires significant engineering resources and costs 30%–40% of the overall expenditure.

An afterthought: For decades, the testing strategy has been put off until the end of a product cycle, which is too late and can cause release delays and budget overruns.


DevOps and intelligent automation, as well as the proliferation of digital applications, have considerably challenged traditional techniques for application testing in recent years. Delivery times have gone from months to weeks, and nowadays, testing has moved to the left and right of the software development lifecycle. Agile and DevOps have combined development and testing into a single, continuous process. Quality engineering has changed from testing to starting with the planning of the first application. It creates a constant feedback loop that lets you plan for the unexpected and act on it.

However, to properly comprehend the magnitude of the evolution from testing to quality engineering, we should first recognize how data has impacted software development. Data can do more than just power automation use cases and AI learning datasets for repetitive development and testing processes. The enormous amounts of data users create daily to make it more important for quality engineers to predict risk, find opportunities, increase speed and agility, and reduce technical debt.

Quality engineering is changing in tandem with the ever-increasing cyber security concerns. Today’s quality engineering role must enable faster application, product, and service delivery and act as an enabler, not a barrier, to digital transformation.


As these changes in quality, technology, people, and organizations take hold, QE will grow into a role that is more pervasive, real-time, and based on insights. AI-led autonomous frameworks will support this to make sure business continuity and value. Testing will evolve away from traditional ways and toward new ideas and methodologies appropriate for the application engineering world of the future across five dimensions: data, frameworks, process, technology, and organization.


Today’s rapid growth of enterprise application testing environments shows no signs of slowing. As it evolves, QE’s focus on apps will be less defined by its alignment with business objectives. This means testing, monitoring, and making real-time fixes to ensure that the business “works” as well as the code. It also entails creating self-learning, self-adapting systems assisted by machine learning and advanced analytics.

Tavant is actively planning for this future. We are propelling QE into the future with breakthroughs in holistic QE strategy, incorporated cognitive and machine learning capabilities, and end-to-end automation. This changes everything, from test planning and test case development to test execution and environment setup, and it helps QE reimagine its role in the future enterprise.

Tavant Quality Engineering Services helps organizations engineer quality into their processes by incorporating a whole gamut of services, tools, and techniques to elevate the end-user experience.

AI-Powered Next-Gen Test Automation Framework

Tavant’s AI-powered next-gen test automation platform, FIRE  (Framework for Intelligent and Rapid Execution), is Tavant’s proprietary suite of solution accelerators aimed at optimizing the overall testing effort and delivering a high-quality product. It is a comprehensive tool and technology agnostic-test automation framework. This framework can orchestrate multiple automation tools and technologies, including (but not limited to) Selenium, Appium, Cypress, Protractor, Microfocus and Java, C#, F#, Python, and PHP.

The test automation framework ensures speed to market and superior quality software. FIRE 5.0 accelerates the time to market while simultaneously aiding developers to enable a dual shift of the software development lifecycle to gauge the consumer experience and provide continuous feedback into the system. It offers comprehensive test automation coverage and efficiency of more than 90%.

Importance of Quality Assurance & Testing in the Finance Industry

The financial industry is on the verge of transformation. Mobile banking, investment, insurance, app payments, advances in technologies such as cloud, mobile, AI, agile, and DevOps, and concerns about fraud detection management, data visualization analytics, risk and compliance management, and digital lending require specialized testing.

Tavant’s Quality Engineering Services have been designed with the financial industry in mind. Our quality engineering services can help you with an error-free application and accelerate your time to market at a lower cost.

Visit here to learn more.

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