By AI Trends Staff  

Machine learning has the potential to automate many more business processes than are currently automated in enterprise software, based on all the previous generations of software development methods.   

That is a suggestion put forward by Claus Jepsen, chief technology officer at Unit4, an ERP software supplier based in Denmark.   

“Based on my experience, typically less than 20% of business processes are automated in enterprise software. I believe that in as little as two to three years, we could see up to 80% of routine business processes automated by ML,” Jepsen stated in a recent account in Forbes. 

Much of machine learning, which he describes as the ability to create automation through AI algorithms, is statistical analysis from crunching numbers, identifying patterns and predicting future outcomes based on past results. All this can be done with standard logical programming.   

The degree to which ML can improve the business outcomes is “currently marginal,” he suggests with accuracy of financial forecasts, for instance, sensitive to many greater factors than how well the algorithm can refine itself over time. If you haven’t got harmonized, accurate and complete data to start with, simply applying ML to it isn’t in itself going to result in better business decisions,” Jepsen stated. 

Defining the business problem is the same challenge that has always faced software developers. “In terms of Gartner’s hype cycle, ML is currently at the peak of inflated expectations,” he stated. “You cannot simply throw ML at a bucket of big data and expect it to magically come up with a perfect business plan.”  

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