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The current IT landscape demands faster time to market with a high level of customer satisfaction, but in a cost-efficient manner. Needless to say, software testing becomes a critical activity to accelerate releases. Test automation has helped in achieving this goal to some extent, especially in terms of time management and quality assurance. However, it still needs to do better when it comes to cost-effectiveness and overall efficiency. That is where intelligent test automation steps in. We have discussed the benefits of intelligent test automation in detail in our blog.
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Managing QA Cost By Adopting Intelligent Test Automation The current IT landscape demands faster time to market with a high level of customer satisfaction, but in a cost-efficient manner. Needless to say, software testing becomes a critical activity to accelerate releases. Test automation has helped in achieving this goal to some extent, especially in terms of time management and quality assurance. However, it still needs to do better when it comes to cost-effectiveness and overall efficiency. That is where intelligent test automation steps in. We have discussed the benefits of intelligent test automation in detail in our blog.
Factors driving the cost in software testing As per the world quality report 2021-2022 by Capgemini, the global pandemic has spurred digital transformation programs worldwide, leading to the rise in demand for high-quality and reliable applications/products. Consequently, the pressure on the quality assurance budget has increased.
How intelligent test automation manages cost • As stated in the previous section, the organizations are earmarking bigger IT budgets, so naturally, the general expectation is to maximize the benefits. Investing in AI-augmented software development is another aspect that is gaining importance due to its efficiency, reliability, and better ROI. The findings of another survey by Gartner Inc. for the increase in industry-wide funding for AI in 2022 are shared below. Organizations are heavily investing in AI and there is a good reason for it. The stakes involved are pretty high.
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