“The days of enterprise IT telling employees what they can and cannot do with their devices are over,” says Christian Reilly, CTO of Workspace Services at Citrix, a leader in Secure Digital Workspaces. “The simplicity of consumer IT has been the biggest driver of its success – think of how easy it is to access Amazon from any device and buy whatever you like. That revolution is now coming to the workplace,” adds Reilly. Services such as Amazon are naturally intuitive. It is like a phone: it just works. That is the antithesis of traditional enterprise IT, where applications and systems were difficult to use and required a lot of expertise.
Many organizations today are using the so-called hybrid cloud approach, accessing different IT services from different cloud providers, plus continuing to operate some on-premises infrastructures. For employees to be more productive, you need a combination of back-end systems that can understand who they are, what device they are using, where they are, and what they are trying to do at a certain time. The challenge is to create a secure digital perimeter around all those services and the devices used to connect to them, while giving end users a simple and unified experience. This is what we do with Citrix Secure Digital Workspace – it enables secure access to any application on any device from any network.
Machine learning, which is part of AI, helps construct models of what people do by creating a pattern of their everyday activities. Companies could use machine learning to model how their employees behave in different contexts, understand what they need to perform better, and give them the information they need to be more productive. With Siri, Cortana, Bixby, Google Assistant, and Amazon Echo, we’re seeing the next generation of the human-computer interface, based on voice recognition and natural language processing. In the future, we could even speak to enterprise data directly rather than having to fill in forms or write complex reports. The potential for productivity is massive.
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