The perception is that artificial intelligence (AI) is one of those arcane sets of technologies that only benefit organizations that have a few extra million dollars available in their IT budgets to explore the esoteric. In reality, AI is starting to be infused in some of the most widely used applications among small-to-medium businesses (SMBs).
Oracle NetSuite today at a SuiteWorld18 conference unfurled an update to the business intelligence (BI) modules made available as part of the company’s cloud application suite that is now infused with machine learning algorithms.
Jason Maynard, senior vice president of marketing and strategy for Oracle NetSuite, says that while AI and machine learning algorithms may be overhyped, the fact is these technologies can now analyze mountains of data to surface up more accurate recommendations that shouldn’t be ignored. For example, finance professionals can take advantage of machine learning algorithms to improve audit risk analysis, analyze past payment histories and enhance cash flow predictions. Similarly, human resource professionals can employ machine learning algorithms to create profiles of the best performing employees that can then be used to predict future high performers.
At the same time, Oracle NetSuite today also revamped its e-commerce application with a goal of enabling SMBs to access an integrated e-commerce that will enable them to stand up an online store in less than 30 days.https://o1.qnsr.com/log/p.gif?;n=203;c=204663295;s=11915;x=7936;f=201904081034270;u=j;z=TIMESTAMP;a=20410779;e=i
Finally, OracleNetSuite is moving to make its applications available on a global basis. Localized instances of Oracle NetSuite applications are now available in Germany, France, China, Japan, Brazil and Mexico.
“The flag is going to be planted everywhere,” says Maynard.
It’s apparent that as more business processes are shifted into the cloud, the ability to apply machine learning algorithms globally could level much of the playing field between SMBs and large enterprises. The only challenge now may be determining which business processes to apply those algorithms to first.