Every year Dejan Milojicic, a well known IEEE volunteer , former president of the Computer Society and Distinguished Technologist at Hewlett Packard Labs, try to herd a clowder of cats (technologic cats) to come up with predictions on what technologies will set a mark on the coming year.
The result has just been published by the Computer Society Magazine, “IEEE Computer”, and it makes for a good reading.
You get a feeling on drone delivery, digital twins as bridge between the physical and virtual worlds, non-volatile memory, AI applied to cybersecurity, security and privacy in the age of big data and Machine Learning, and much more (even a discussion on Arts, Science and Fashion!). As a wrap up you can also find an article on Prediction on Predictions where the previous predictions are discussed and rebutted. As I said, the whole package makes for a good reading.
Making technology prediction on a one year horizon is not that difficult. You observe what is going on now and look for signs of alternatives or market/industry interest, then you can draw a linear roadmap that will be pretty accurate for the next year. This is true for evolutionary technology, marking an improvement on actual ones. It is not rocket science to predict that next year smartphones will have more processing capacity, will embed more storage capacity and will include 5G. You can actually save your prediction text and reuse it for the coming 3 to 4 years (6G is way in the future).
Saying that Digital Twins are going to be used more and more by industry is also a no brainer. The big guys have adopted them and the small ones have to align… However, predicting that they will be adopted in the healthcare area is not a given because here it is no longer about technology alone (tech is available, no question about it) it is about regulation and processes (very strict, viscous, and complex in the healthcare domain). Predicting that cognitive digital twins will make way in education is just a wild guess, may be a wishful thinking, because here there are many uncertainties involving societal questions.
Actually, if we restrict our sight to technology adoption by industry the main force is the existence of industrial “tools” supporting the smooth, seamless, introduction of the technology in a specific industry (and industrial process). For Digital Twins we can be confident on their increased adoption because there are now industrial platforms, like MindSphere (Siemens) and GENIX (GE) supporting them.
Tools, processes, framework aggregating industrial ecosystems make adoption possible but what makes it happen and speeds it up are economic factors. Of these the possibile decrease in manufacturing (more generally production) cost leads adoption. The possibility of generating additional revenues follows as good second. Making prediction based on cost decrease is straightforward, making them on revenue increase is way more tricky.