AI (Artificial Intelligence) and ML (Machine Learning) are the number one strategic enterprise IT investment priority in 2018 (named by 33% of enterprises), taking the top spot from container management (28%), and clearly leaving behind DevOps pipeline automation (13%), according to new Enterprise Management Associates (EMA) research.
At the same time, most enterprises are still struggling to understand the basics of how to successfully evaluate AI and ML solutions, how to put project performance metrics in place, and how to handle the eight key limitations of AI and ML technologies today, says EMA.
Some of the key benefits of artificial intelligence and machine learning identified in the research are:
■ Free up 30% of developer time and up to 50% of IT operator time used to support infrastructure
■ Eliminate operational silos as the root cause of cost, quality, and speed bottlenecks in DevOps
■ Proactively address operational issues and minimize mean time to repair (MTTR)
■ Curb alert flood and receive earlier alerts aligned with business priorities
■ Help the 72% of enterprises with ungoverned Kubernetes clusters to bring these back under corporate control
■ Operate a mostly self-driving hybrid cloud to unlock the 50% of data that cannot go into the public cloud today
■ Improve collaboration between developers, IT, and business
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