It's the beginning of September (and no, I don't know how that happened either), and as the summer lull winds to a close and we prepare for a renewed frenzy of activity, it's a good moment to take stock of the year so far. Last month, two different articles were published looking back over some of the key trends we've seen in 2018 with regard to emerging technology and digital transformation, and comparing them to what was predicted. One was a piece by Forbes contributor Daniel Newman of CMO Network, who revisited his predictions for digital transformation in 2018 in light of the past eight months, to see where we are with some of 2018's most potentially transformative technologies. It takes a broadly optimistic view of the technologies that are meant to be shaking up the digital world in 2018, with a few caveats. The other was by The Register's Andrew Orlowski, written in response to the publication of Gartner's annual'Emerging Technologies Hype Cycle', which revealed that a number of the most "hyped" technologies from last year have vanished from this year's chart.
Every year brings a new set of hyped technologies. It often seems like everyone is talking about them, even if we don't all understand just what they are or what they do. For instance, in recent years everyone was talking about blockchain, even as there were very few in-production examples of what it did and how it worked. Yet it seemed that everyone needed to have a blockchain strategy. The Gartner Hype Cycle for Emerging Technologies tries to categorize emerging technologies like this by where they are on the "hype cycle," a hero's journey for technologies, from the innovation trigger to the peak of inflated expectations, on through the trough of disillusionment to the slope of enlightenment and finally to the plateau of productivity.
According to the 2016 Gartner Hype Cycle for Emerging Technologies, machine learning is at the very "peak of inflated expectations," the highest point in the S-curve that Gartner awards technologies in its Hype Cycle reports. Many machine learning advocates may feel betrayed to think that machine learning is at the peak of its hype cycle, thinking that analysts like Gartner believe machine learning to be all fluff and no substance. But that is not the case. Many emerging technologies never actually make it to the peak of the hype cycle, fizzling out long before they can make a true impact. In reality, technologies that make it to the peak of the hype cycle are almost ready for universal deployment.
Want to know how survive and thrive in the digital economy over the next five to 10 years? Gartner has just published its Hype Cycle for Emerging Technologies, 2017 and identified three "megatrends" you need to be aware of: I'm going to guide you through them. This is going to be a long read because I'm sure, like me, you're reading about these topics. As professional communicators we need to understand these areas to know what to implement for our organisations and clients. It's important to me to provide clarity through my blog, so I'm going to jargon bust as we go.
Every year, Gartner, a leading industry analyst firm, releases a report called the "Hype Cycle on Emerging Technologies." The purpose of the report is to identify up-and-coming technologies and visualize how close they are to becoming mainstream. The Hype Cycle is a graphic representation of the path that a technology goes through from obscurity through hype to stabilization and mainstream use. In 2016, at the top of this hype cycle was the term machine learning. This means that machine learning is a hot topic across all industries.