Digital twins have been around for decades. They are making a huge impact as of late with the rapid rise of IoT, as they’ve become more widely considered as a tool for the future. Digital twins are getting their just due because they are especially good at integrating things like artificial intelligence (AI) and machine learning. They bring data, algorithms, and context together, enabling organizations to test new ideas, uncover problems before they happen in the real world and monitor numerous devices remotely. And as digital twins are bringing more assets together, and combining them with information about processes and people, their ability to help solve complex problems is increasing exponentially. The following article describes specific use cases where digital twins are making a difference.
For the past several years, the internet has been ringing with a new buzzword: digital twin. And, more recently, the term “digital twin of an organization (DTO)” has been added to the mix—as seen by Gartner’s move to add DTO to its list of top ten strategic technology trends for 2019.
As digital twins grow in complexity and move from being digital representations of single items to models of systems of interconnected things, more businesses are seeing the technology as an opportunity to orchestrate people, processes, and things in a sophisticated way, resulting in better business outcomes, as well as benefits for everyone. But is digital twin technology really here to stay? And where do its biggest opportunities lie for the future?
