Hyper-automation
Hyper-automation elevates task automation to the next level. It is the application of advanced technologies like Artificial intelligence (AI) and Machine learning (ML) to automate processes (not just tasks) in ways that are significantly more impact than that of traditional automation capabilities. It’s the combination of multiple machine learning, packaged software and automation tools to deliver work. Hyper-automation requires a combination of tools to help support replicating pieces of where the human is involved in a task. This trend kicked off with robotic process automation (RPA) but will see growth with the combination of process intelligence, content intelligence, AI, OCR and other innovative technology.
Multi-experience
Multi-experience deals with the massive shift from a two-dimensional screen and keyboard interface to a much more dynamic, multi-modal kind of interface world where we’re immersed in the interactive technology and it surrounds us. Multi-experience currently focuses on immersive experiences that use augmented reality, virtual reality, mixed reality, multi-channel human-machine interfaces and sensing technologies.
AI enabled conversational platforms have changed the way in which people interact with the digital world. Beyond conversations, virtual reality (VR), augmented reality (AR) and mixed reality (MR) are changing how people perceive the digital world. This combined shift in both perception and interaction will result in the future multi-sensory and multi-modal experience. Over the next decade, this trend will become what is known as ambient experience.
Democratization of Technology
Democratization of technology refers to the process by which access to technology rapidly continues to become more accessible to more people.
The democratization of technology means providing people with easy access to technical or business expertise without extensive or expensive training. This is already widely recognized with the rise of the citizen developer. Historically, automation was managed and deployed by IT, but the emergence of robotic process automation has changed that with the emergence of digital workers. We are now seeing a new generation of citizen developers, such as business analysts, who are closer to business challenges and can program and automate digital workers to help them do their work.This trend will focus on four key areas: application development, data and analytics, design, and knowledge. According to Gartner, these may be tools designed “to generate synthetic training data, which helps address a substantial barrier to ML model development.”
New technologies and improved user experiences will empower those outside of the technical industry to access and use technological products and services.
