One of the frustrations that I hear when I talk to contacts in mining, oil and gas and infrastructure spheres is how to apply new technologies as such as AI to their relevant situation. I ask if they have heard of the Gartner Hype cycle – which comes from the software development and information technology space. This post provides an overview of the hype cycle and linking this to some of the concepts around technical and commercial readiness utilised in applying technology to the real world.
I find the Hype Cycle developed by Gartner, is a great illustration of how digital technology is developed, evolves and then is scaled into mainstream adoption.
Gartner, who is a research and advisory firm that focuses on business and technology topics, provides research into a range of technologies and I would encourage you to review their information on the Hype Cycle and their YouTube video introducing the hype cycle. Of topical interest is the development of different AI technologies which they describe in these articles.
Technology Readiness
The fact that many of my colleages in the technical areas, not involved in software are not aware of the Hype Cycle, made me think of what is fulfilling this space. The equivalent is the technology readiness levels which dates back to the cold war systems engineering work at NASA from the mid-1950s to the early 1970s.
One key concept to keep in mind, is that systems can be broken into sub-systems, and this assists in understanding the elements that require focus or additional investment to apply them to your particular implementation or requirements.
In Australia, the Australian Renewable Energy Agency (ARENA) has developed a guide to assess the readiness of renweable energy projects. There are many adaptions and visualisations of the technical readiness and comercialisation available, but here is my adaption of this information, mainly from the ARENA guide mentioned.
Summary
There are a lot of parallels in terms of the Hype Cycle and the technology readiness levels in conjunction with commercialisation and implementation of technology. Information Technology (IT) or digital applications project notoriously have a high failure rate for a number of reasons – too numerous to mention here and probably a topic for another post.
There are clear risks, which can be managed with appropriate design, development, resources, time and testing – very dependent on your situation and challenges. In some ways the Hype masks the true level of maturity of a technology and boards, executives and decision makers feel as if they are pressured into being seen to doing something leading to questionable value being leveraged from the investments made in this space. This certainly is the case for AI applications, and Gartners research in this space shows that there is some development still to go with the use cases in this space.
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