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Augmented Technologies: Flavoring Your Software with ML and AI
“New and Improved” doesn’t have the right ring any more in the world of business software. As software improves, even if incrementally, marketing forces the monikers to change.
There was a period of time where ‘2.0’ was the signal for cutting edge software: Web 2.0, Business Process Engineering 2.0, Content Management 2.0, Analytics 2.0, and even more recently Software 2.0.
‘Intelligent’ has been a popular adjective for a long time that’s still tacked onto ‘next generation’ software revisions, like intelligent analytics, intelligent character recognition, intelligent Content Management, etc.
One new trend is to use the word ‘augmented’. Gartner has taken the lead with names like augmented analytics and augmented data management, two of the top trends that Gartner has identified developing in 2020.
‘Augmented’ means that the software is enhanced by integrating with elements of machine learning (ML) and AI. Augmented software can supposedly self tune and optimize. Augmented data management, for example, can enable greater amounts of automation, metadata self-classification, and eliminate redundant and tedious data management tasks.
Kurt Muehmel, New York City-based Dataiku’s chief customer officer, notes that while ‘augmented’ AI capabilities is an improvement over previous software generations, at this point it is more of an incremental improvement rather than a revolution. Muehmel said that “the reality of most augmented analytics or AutoML tools and systems today is that they are not completely automatic, as the pre-built automation solutions don’t fit the needs or regulatory requirements of the business.”
