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AI and the Human Touch: Maximizing IT Issue Resolution

IT operations teams should work with IT service teams, data scientists, and machine learning experts doing the heavy lifting on the build side.

Artificial intelligence can be a game changer when it comes to IT issue resolution, particularly in cloud environments, creating massive productivity gains for organizations. Technology solutions rooted in AI empower teams to monitor and optimize their entire hybrid, multi-cloud topology in real-time.

AI — especially deterministic or causal AI — can be used to observe behaviors, search for anomalies and degradations with true business impact, and instantly alert teams when problems occur and point to the root cause.

Andi Grabner, DevOps activist for Dynatrace, says AI and automation can eliminate the need for human intervention to solve basic IT problems. "This frees up time for teams to engage in more complicated issues where their time and touch is more meaningful and offers greater value," he says.

In this way, AI augments people to perform at a higher level than is otherwise possible.  

"Teams also need to ensure their AI is drawing the correct conclusions, making the right decisions, and implementing the right solutions," he adds.

Benefits Already Made Clear

Melissa Herrle, vice president of product at OpsRamp, points out AI benefits in IT issue resolution are already being seen today, mainly in reducing alert noise and help desk tickets.

"Intelligent alerting and event correlation ensures that multiple tickets aren't being filed for the same event," she explains. "This leads to a reduction in mean time to detect and resolve. This is typically the first benefit customers see from an AIOps implementation."

Herrle says the smarter the AIOps system becomes, the more the organization can automate processes in response to detected events, be they automated remediation or just automatically directing the right internal resources — human or machine.

"The biggest limitation is data," she says. "The more tools in use, the more data has to be collected, filtered and managed, and the more data accuracy issues you'll have."

Read the rest of this article on InformationWeek.

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