We may be years away from the “AI-enabled Coworker,” but the first implementations of machine-learning capabilities are finding their way into the everyday data-analysis tools used by businesses of all types. Cognitive assistance promises to reshape business processes, but only if app development and deployment tools are adapted to support machine learning.
While it has become fashionable to hypeAIas the next game-changing technology promising to have an impact greater than either mobile or cloud, the reality is that machine learning will be a long time coming to everyday business analytics. As with any sea change, cognition is likely to sneak its way into applications and processes in drips and drops. It looks like this year could be the year many businesses get their first hands-on experience with cognitive-learning business apps.
For example, IBM’s Watson elicited plenty of “oohs” and “aahs” when it beat the Jeopardy champions, but the AI-based platform drew praise of another sort with the introduction of business solutions at the recentWorld of Watson event, as NewsFactor pointed out . Watson’s professional series applies cognitive learning to the analysis of large data sets; it works in tandem with enhancements to IBM’s DB2 for transactional processing in analytical databases.
IBM may have gotten a bit of a jump on the field of vendors racing to bring machine-learning capabilities to business processes, but the contest has just begun. The real winners are line managers, who stand to benefit the most from AI-enabled business applications.
Some opinions expressed in this article may be those of a guest author and not necessarily Analytikus. Staff authors are listed https://www.datasciencecentral.com/profiles/blogs/machine-learning-poised-to-impact-business-analytics-in-2017
