{"id":42796,"date":"2026-01-02T06:57:17","date_gmt":"2026-01-02T11:57:17","guid":{"rendered":"https:\/\/centricconsulting.com\/?p=42796"},"modified":"2026-03-10T15:03:11","modified_gmt":"2026-03-10T19:03:11","slug":"using-ai-in-software-testing-to-improve-automated-testing","status":"publish","type":"post","link":"https:\/\/centricconsulting.com\/blog\/using-ai-in-software-testing-to-improve-automated-testing\/","title":{"rendered":"How AI in Software Testing Improves Test Automation and Accuracy"},"content":{"rendered":"

People are fascinated by AI and ChatGPT and are looking for better ways to use it. In the tech space, some people are discussing how these tools are transforming software and testing, but many overlook a key point: AI in software testing is not new. Long before ChatGPT, teams were already using AI to improve automated testing, increase accuracy, and reduce manual effort.<\/span><\/h2>\n
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Artificial intelligence (AI) has been portrayed in pop culture as a technological threat for decades. From HAL in <\/span>2001: A Space Odyssey<\/span><\/i> to Skynet in <\/span>The Terminator<\/span><\/i> and VIKKI in <\/span>I, Robot<\/span><\/i>, AI often appears as the villain in our imagined future.<\/span><\/p>\n

These portrayals reflect a deeper fear: that technology will replace humans. AI-powered systems are already taking over tasks once handled by factory workers and call centers, and increasingly by knowledge workers, including those in software development and testing.<\/span><\/p>\n

Still, for much of my career, many people listed me as an anti-automation person. I find this interesting because I use various automation tools to assist me in my testing work, even if I don\u2019t use trending name-brand tools. The reason is simple \u2013 those tools often didn’t do what I needed without a lot of extra work.<\/span><\/p>\n

The Rise of AI in Software Testing<\/h2>\n

I am wary of the new, buzzword-laden solution people hail as the next great thing to improve the software world. Early automation tools that did record-and-playback and nothing else were similarly acclaimed. The industry also praised the next several <\/span>test automation<\/b><\/a> tools that fixed or avoided the problems of earlier tools.<\/span><\/p>\n

Before I go all-in on a revolutionary tool or approach, I want to see real, repeatable evidence that it works as described. <\/span>I have seen too many people, teams, and companies burned by trusting initial advertising.<\/b><\/p>\n

The cool, new, attention-grabbing thing is <\/span>ChatGPT and AI <\/b><\/a>in software testing. So, let\u2019s talk about it.<\/span><\/p>\n

Understanding AI Software Testing and ChatGPT<\/span><\/h2>\n

AI is powered by three key elements: large volumes of data, significant computing power, and an underlying model determining how the AI learns. This model drives the learning algorithms and processes the data, generating results.<\/span><\/p>\n

Most software professionals already interact with AI through everyday tools. For example, search engines may not feel like artificial intelligence, but their ability to refine results based on repeated queries is a common form of AI in software testing workflows. The more often users search using similar terms and click on specific results, the smarter the tool becomes at anticipating intent.<\/span><\/p>\n

ChatGPT, a generative AI tool, takes things a step further. Instead of simply retrieving results based on search keywords, it generates original responses to user prompts.\u00a0 <\/span>This allows software teams to:<\/b><\/p>\n