Systems | Development | Analytics | API | Testing

Earlier this year, SmartBear acquired QMetry, a move that’s more than just a strategic acquisition. This move reflects a deeper commitment to enterprise customers – helping teams: As Product leader of Test Management at SmartBear, I’ve had the opportunity to help define our roadmap. Our vision for QA teams is clear: empower them to deliver better quality and build confidence – and consistently hit release deadlines.

As enterprises increasingly embed AI assistants into their core workflows, trust becomes the currency of adoption. Salesforce Einstein Copilot is fast becoming a central productivity layer across CRM, Sales, and Service modules. But with great potential comes greater responsibility, especially for quality assurance teams. Validating the trustworthiness of AI outputs, guarding data privacy, and ensuring reliable decision boundaries are now non-negotiable in enterprise environments.

Gone are the days when core banking teams relied solely on long-winded manual test cycles, midnight war rooms and crossed fingers before a go-live. Today, the industry stands at the edge of a seismic shift, driven by the power of test automation. Having worked extensively in the complex and highly regulated world of core banking systems, we’ve seen this transformation unfold firsthand.

Software development has never been more dynamic. With rising complexity, fast deployment cycles, and remote collaboration, developers now rely heavily on powerful tools to streamline their workflows. From writing and testing code to deploying and managing applications, the right set of tools can significantly boost productivity. In 2025, the integration of AI into developer tools is transforming how software is built.

Automating QA testing helps ensure your website works flawlessly for every user, on every device, under every condition. From login flows to checkout carts, test automation gives teams the speed and confidence to ship frequently without breaking things. In this guide, you’ll learn what automated QA testing is, why it matters, which tests to automate, and how to build a reliable automated QA testing process from scratch.

Every organization, regardless of the size or industry, has AI Ambitions. While this is an exciting and revolutionary time, it’s also filled with uncertainty and risk. At Perforce, we see what customers are facing. Organizations need to develop a clear and focused AI strategy that articulates the vision and value that AI can provide to the business. Security and compliance need to remain front and center, and vendor trust is essential.

AI is becoming a crucial part of how we build software. From recommending products to helping businesses predict what their customers might need, AI is changing how we think about building and using apps and software’s. The wide variety of libraries and frameworks available in the Java ecosystem will bring developers powerful, specific tools for creating AI applications that enable a variety of subjects, including machine learning and natural language processing.

UI testing services can help teams ship code faster while ensuring no bugs immediately obvious to users make it into production. However, many testing services can’t deliver these benefits for various reasons (which we’ll discuss in more detail below), the main one being that their automated tests don’t validate an application’s UI directly, like how a real-life user would by clicking buttons, pages, form fields, and other UI elements.