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By Kevin Surace  | AI, Generative AI, Predictions, Scription

Generative AI is Here in Testing

Generative AI is a type of artificial intelligence (AI), one of many, where it is trained on a very large set of data. After training, if you give it some direction, it generates something for you.

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And How AI-First QA Helps Mitigate the Risks Software is the backbone of nearly every enterprise—powering everything from internal operations to customer experiences. But with this reliance comes risk. Software defects are no longer minor annoyances; they are massive liabilities, costing businesses billions each year in lost revenue, customer churn, legal penalties, and reputational damage.

Real-World Examples and How AI-First Testing Can Save Millions When it comes to software development, the cost of a failure isn’t just technical—it’s financial, reputational, and often irreversible. From broken login flows and crashing apps to compliance violations and data leaks, the price of undetected defects can cripple businesses. That’s why forward-thinking teams are turning

In today’s hyper-competitive digital economy, software isn’t just a support function—it’s a core business driver. Whether it’s a banking app, an e-commerce checkout flow, or a SaaS platform, users expect flawless digital experiences. One bug, one crash, or one frustrating delay can result in lost revenue, damaged brand reputation, and diminished customer trust. That’s why

When it comes to software development, delivering new features quickly often takes priority over long-term code quality. As teams race to meet deadlines, testing can become an afterthought—leading to bugs, fragile code, and an accumulation of technical debt. Over time, this debt slows velocity, increases maintenance costs, and makes innovation harder. But what if you

Continuous Integration and Continuous Delivery (CI/CD) have become the gold standard for modern software development. By automating the build, integration, and deployment process, CI/CD pipelines enable teams to move faster, release more frequently, and respond to change with agility. But there’s a critical piece often missing in this streamlined process—Continuous Testing (CT). Without continuous, automated

Testing is no longer confined to the QA department—it’s now an integral part of every stage of the software development lifecycle. The “Shift Left” and “Shift Right” testing philosophies have emerged as essential strategies for delivering high-quality software faster, with fewer bugs and greater user satisfaction. But implementing both effectively—catching defects early while also validating