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Hype Cycle of Artificial Intelligence

Introduction of Gartner Hype Cycle


It is always highly speculative when trying to assess the impact of a research area or new technology on the future as the future prospects will always be biased by previous experiences. Therefore, we do not attempt to predict the long-term future of AI. Nevertheless, we want to examine the directions of developments in AI and the supporting technologies.


The Gartner Hype Cycle is a graphical representation of the maturity, adoption, and social application of specific technologies. The Hype Cycle provides a visual representation of the overhyped nature of emerging technologies. It is used to identify the stage of a particular technology.



Gartner uses the Hype Cycle, a leading market research and advisory company, to track the adoption of new technologies and to help organizations understand the potential impact of these technologies on their operations. The Hype Cycle is updated annually and covers a wide range of technologies, including emerging technologies such as artificial intelligence, blockchain, and the Internet of Things.


What is the Hype Curve?


The Gartner hype curve is frequently used to evaluate the potential of new technologies. The hype curve is presented in a diagram where the y-axis represents the expectations toward new technology and time is plotted on the x-axis.


Five Phases of Hype Curve


The Hype Cycle is based on the premise that new technologies go through a series of stages as they are adopted by the market. These stages include the innovation trigger, peak of inflated expectations, trough of disillusionment, slope of enlightenment, and plateau of productivity.


1. Innovation Trigger

The innovation trigger is the stage in which a new technology is first introduced and begins to generate buzz. This is typically the point at which technology is first demonstrated or becomes available for purchase.


2. Peak of Inflated Expectations

The peak of inflated expectations is the stage in which the hype around a technology reaches its peak and the technology is expected to solve a wide range of problems. This is often the point at which the technology is overhyped and unrealistic expectations are set.


3. Trough of Disillusionment

The trough of disillusionment is the stage in which the hype around a technology begins to wane and it becomes clear that the technology is not living up to its hype. This is often the point at which the technology is abandoned by early adopters.


4. Slope of Enlightenment

The slope of enlightenment is the stage in which the technology begins to mature and its true capabilities and limitations become clearer. This is the stage at which the technology is more widely adopted and begins to deliver value.


5. Plateau of Productivity

The plateau of productivity is the stage at which the technology becomes widely adopted and is used in a productive manner. This is the point at which the technology has reached mainstream adoption.


Artificial Intelligence Trend 2021

  1. In the innovation trigger phase, subjects like composite AI and general AIappear. Moreover, topics like Human-Centered AI and Responsible AI show that human integration is becoming increasingly important for the future of AI.

  2. Deep Neural Networks, which have been the driver for new levels of performance in many machine learning application over the past decades, are still at the peek phase of inflated expectations. Moreover, topics likeknowledge graph and smart robots appear in that phase.

  3. In the disillusionment phase, we find topics like autonomous vehicles andchatbots, which have experienced defunding as the high expectations in this are could not be met.



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