Artificial Intelligence and Machine Learning in data analytics and business applications

Artificial Intelligence and Machine Learning in data analytics and business applications


Artificial Intelligence and the sub-set of it which is machine learning are hot. It’s been impossible to attend an IT conference in the last year or so without encountering a dead human genius reincarnated as a software system or a robot.

What lies beyond the hype? In the data management field, experts tell us there are many basic things organisations can do to get more business value from their data before they over-commit to experimenting with machine learning.

And yet, as the articles in this e-guide show, there is real worth in AI/ML, and it might open up new roles and more business-central activities for IT professionals. This is suggested in the lead article here, which explores the impact AI/ML is having in the Law, and suggests parallels in other sectors. However, the potential for AI to take away, but fail to replace jobs should not be ignored, and needs to be understood and managed.

A recent McKinsey study suggests adoption of AI/ML is fairly modest outside the technology sector itself, but does indicate significant investment. And there does seem to be a concatenation of technologies – blockchain, IoT, machine learning that might, together, transform the business applications side of IT more broadly.

SAP and IBM are among the suppliers investing in artificial intelligence and machine learning. The latter is showcasing some of its Watson AI capability at Wimbledon this summer. But all the enterprise software giants are pitching in and one of the articles in this e-guide counsels against too hasty adoption of a “black box” approach”.

04 Jul 2017
04 Jul 2017
53 Page(s)
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