New technologies are frequently discussed today in terms of how fast they can deploy and how greatly they can impact different markets. Gartner invented the famous “hype cycle” to explain this very phenomenon. The chart presents the input of thousands of C-suite staff in anticipating how new technologies will impact our world.
For a while, Gartner included a variety of flavours of AI: from deep learning to Artificial General Intelligence; from Edge AI to AI PaaS. The lack of strict scientific approaches to this measuring process will always lead us to suspect that large consultant firms focus more on exciting peaks of potential technologies than more realistic deployment plateaus. Ironically, the perceived intuitions of such decision-makers and subsequent investment decisions can make some of these prophecies about expectant technologies self-fulfilling.
We all want AI to be implemented faster and to better impact our fields, but half of all executives say it will still take more than three years before they see a significant return in the investment of AI, KPMG reports. The number is less optimistic than previous years as industries begin to realise that the implementation path of AI projects in business is significantly slower and harder than expected.
That said, KPMG consultants see still significant investments from companies who trust that their data platforms will provide significant returns in due time. As such, many companies make these investments without a clear idea of how their businesses will integrate AI initiatives.
In any case, the notes from the KPMG interviews are worth reading. The same firm recently released an interesting report on Intelligent Automation, a concept that basically combines AI with robotics and introduces a new acronym: IA.