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15-06-2020 - - 0 comments
5 Things the Current Gartner Hype Cycle Tells Us

One of the main tools that try to capture the state of the technology market and industry is the annual Gartner Hype Cycle. As you probably know, the Gartner Hype Cycle for Emerging Technologies is a leading authority in technology trends. The first publication was in 1995 and Gartner has issued an annual report every year.

What Is the Hype Cycle?

In case you aren’t up to scratch on the theory, here’s a quick primer. The Hype Cycle attempts to explain the evolution of technology through several key phases summarised as follows:

·         The emergence of the technology, the “Innovation Trigger”

·         Inflated expectations where there is excessive and sometimes irrational enthusiasm (the model talks of “The Peak of Inflated Expectations”)

·         A period of excessive disappointment known as “The Trough of Disillusionment”

·         A period of gradual, circumspect adoption which the model refers to as "The Slope of Enlightenment" and "The Plateau of Productivity"



(Image source: gartner.com)

Over the years, the Hype Cycle has provided key insights into the direction a new technology is going to take – and, more importantly, provided decision-makers with key information such as:

·         When to invest in innovation

·         Not to ignore an innovation simply because it has failed to live up to its initial hype – it could very well emerge from the Trough of Disillusionment and proceed up the Slope of Enlightenment

·         When to be aggressive and adopt innovations that are a potential game-changer for the business early on

·         When to delay adoption for innovations that have a lower impact on the business

·         Determine investment priorities by analysing the potential benefit of each innovation

The most recent Hype Cycle for Emerging Technologies is the 2019 model shown below.

(Image source: gartner.com)

The latest Hype Cycle picked 29 key technologies from over 2,000. From the chart, we can quickly surmise that the following technologies are on the rise:

·         Adaptive ML

·         AR Cloud

·         Augmented Intelligence

·         Decentralized Autonomous Organization

·         Decentralized Web

·         DigitalOps

·         Emotion AI

·         Explainable AI

·         Flying Autonomous Vehicles

·         Generative Adversarial Networks

·         Immersive Workspaces

·         Knowledge Graphs

·         Light Cargo Delivery Drones

·         Nanoscale 3D Printing

·         Personification

·         Synthetic Data

·         Transfer Learnin


We can also tell that the following are at the peak:

·         5G

·         AI PaaS

·         Autonomous Driving Level 5

·         Biochips

·         Edge AI

·         Edge Analytics

·         Graph Analytics

·         Low Earth Orbit Satellite Systems

While these three are sliding into the trough:

·         3D Sensing Cameras

·         Autonomous Driving Level 4

·         Next-Generation Memory

The latest report also categorised the technologies into five major trends.

Sensing and Mobility

There are several sensing and mobility technologies that are currently going through a phase of heightened expectations. 3D sensing cameras and autonomous driving represent technology that can discern and manipulate objects in the environment.

As artificial intelligence and sensor technology evolves, autonomous vehicles and flying drones will be able to deliver cargo and humans, completely revolutionizing the transport and logistics industries.

Aviation and transport laws in many jurisdictions around the world continue to be the main hindrance to these technologies, hence the reason they are sliding into the trough. But the functionality continues to improve and they are almost certain to move into the slope of enlightenment.

The sensor technology being developed will also further advance the Internet of Things (IoT). Sensors collect troves of data which lead to valuable insights across a broad spectrum of industries and scenarios.

Augmented Human

Augmented human technologies are an extension of 2018’s "Do It Yourself Biohacking" trend. These technologies enhance both the mental and physical abilities of human beings.

They include; augmented intelligence, emotion AI, biochips, personification, and robotic skin. Some of these technologies are expected to lead to superhuman capabilities such as prosthetic devices that give humans incredible strength.

They are also expected to lead to better medical diagnoses and treatments, which eventually lead to longer life spans. Technologies like Biotech (Cultured or Artificial Tissue) will also lead to faster healing of skin, cartilage, muscle and bone, and has potential applications in the medical sports industry.

These technologies are expected to continue to attract interest and enthusiasm for at least five years.

Postclassical Compute and Comms

Changes in the architecture of binary computing have led to faster CPUs, denser memories and greater throughput. 5G, for example, isn’t a new technology but an improvement of current technology, touted to be the missing link in the true ubiquity of low-latency broadband Internet.

Other technologies in this category include low earth orbit satellite systems, nanoscale 3D printing and next-generation memory.

While next-generation memory is seen to slide into the trough, this can be explained by the yet-to-be-solved problem of thermal stress under extreme environmental conditions. The market value for Next-generation memory is expected to exceed USD 12 Billion by 2025.

Digital Ecosystems

These platforms connect people, organisations and APIs and allow seamless communication. They allow decentralised organisations to be more efficient and make it easier to adopt new technologies. Examples include decentralized web, decentralized autonomous organizations, DigitalOps, Knowledge Graphs, and synthetic data.

These technologies are still in the early stages of the curve and are expected to remain so for five to ten years.

Advanced AI and Analytics

This final trend is a recognition of new types of algorithms aimed at better data analysis, insights and predictions. Some of the potential applications of these technologies are not known yet, but all will prove disruptive.

For example, Transfer Learning – where a machine is taught to solve one problem but then applies the same steps to solve a different but unrelated problem – will prove a game-changer in many industries. A lot of these technologies are still in the early stages of the curve and will remain so for a few years.


It’s important to note that in its latest report, Gartner purposely introduced new technologies not mentioned in previous years. This is not to say the technologies are not important but simply a recognition that some technologies have become so essential to business and can’t, therefore, be referred to as “emerging” while others have been featured several times.

While the Hype Cycle is a great tool to see how new technologies emerge and come to market, one of its biggest criticisms is that it can’t predict which technologies will survive and which will fade into obscurity.



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