AI won't replace low-code/no-code tools
According to a new study, 76 percent of tech leaders say that AI will make their existing low-code/no-code tools more efficient instead of replacing them altogether.
The survey from App Builder, with third-party research firm Dynata, finds use of low-code and no-code tools have steadily increased over the past decade and become an integral piece of how 95 percent of teams now build scalable applications.
RPA is not a silver bullet: Why no-code holds the key to digital transformation success
If the UK’s businesses didn’t need to modernize before the pandemic, they certainly do now. The existential crisis many were plunged into over the past two years has reinforced the resolve of boardrooms everywhere that digital transformation is the future. When deployed effectively, it helps to deliver the agility that every business craves, whilst driving the operational efficiencies and productivity gains essential to survival in a period of high inflation and rising costs.
In this context, robotic process automation (RPA) can be a useful tool. But when deployed the wrong way, or in isolation, it may actually end up worsening legacy dependencies rather than alleviating them. Instead, organizations need to think about the bigger picture -- by bringing together apps, automation and extensible integration in a single no-code platform. That’s the best way to achieve modernization at a pace that fits the business.
No code test automation is a game changer
Manual testing of software, no matter how rigorous, poses significant risks to businesses that rely on it. It is time-consuming, prone to human error, and extremely difficult to scale effectively. So why then, when enterprises are increasingly turning to automation to speed up digital transformation, is only 15 percent of software testing currently automated?
Let’s look first at why manual testing is no longer suited to the needs of today’s businesses. With the ever-increasing speed of software development and customization, relying on manual testing alone won’t allow a business to scale effectively. The resource-heavy and time-consuming nature of manual testing can lead to slower release cycles, with companies being forced to cut corners, or not test all their software appropriately. This in turn can lead to systems breaking, and businesses failing to operate as they should. The surge in digital transformation and increased pressure on IT teams has only heightened this challenge, with software needing to be tested 24/7, while everything continues to change.