The traditional approach to private or internal Application Programming Interface (API) integrations, characterized by labor-intensive and error-prone manual processes, is rapidly becoming obsolete. This method, limited by its time-consuming nature and lack of scalability, is giving way to an era of automation. Automated API integrations marks a significant leap forward, offering unparalleled efficiency, accuracy, and the ability to evolve.

The business landscape is undergoing radical change across industries, driven by artificial intelligence (AI) and automation. This article will differentiate AI and automation, debunk misconceptions, and highlight what business leaders need to know to navigate the challenges of integrating AI and automation across the value chain. So what’s the difference between AI and automation? AI and automation have distinct purposes.

Procurement officers in state and local government agencies have a lot of responsibilities, including: It’s a highly strategic role, so it follows that a procurement officer’s time and effort should be spent on decision-making and not on mundane or administrative tasks. Requiring them to focus on tedious tasks like invoice processing is not a good use of their time. It would be akin to expecting a CEO to reconcile receipts against travel reports or to schedule and reschedule meetings.

The landscape of public sector IT is evolving rapidly, driven by initiatives like the Technology Modernization Fund and an increased focus on digital transformation. However, the shift to modern platforms and applications comes with its own set of challenges, particularly in the realm of testing. Traditional manual testing can be slow, error-prone, and expensive. Here are five ways the right automated testing tools can drive public sector IT modernization and accelerate innovation.

Discover the financial benefits of automated testing through the story of Gannett, a media holding company that has saved an estimated $20,000 to date.

In the ever-evolving landscape of software testing, the advent of Artificial Intelligence (AI) has not just been a game-changer; it’s been a paradigm shift. Test automation, once a static process, has metamorphosed into a dynamic and intelligent entity, reshaping how we approach quality assurance.

“According to BrowserStack, around 58% of companies are using visual testing in their QA cycle.” The need for creating high-performing web applications has pushed developers as well as QA teams to establish test methodologies that are ultra-productive. Be it test automation solutions or harnessing value through advanced test practices such as visual testing.