AIOps is an long-term stategy for increasing performance, predicting outages, automating mundane tasks, making reporting actionable, and improving risk management. It's a strategy, not a software, but it does require software support from platforms like Moogsoft, ServiceNow, and Splunk.
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Digital transformation and movement to DevOps and cloud have decentralized IT Operations
This shift has driven the need to improve efficiency. It has enabled frictionless operations that can scale to meet the demands of business. AIOps, or Artificial Intelligence for IT Operations, is a multi-tiered technology approach. It utilizes Big Data Analytics, Machine Learning, and Automation to simplify the way IT Operations teams support and manage modern IT environments to meet these needs.
Every operations management vendor is now claiming AIOps support. This makes the path to achieving business value and transformation in a multi-tiered reality challenging. From over investment into one technology to not aligning the AIOps journey to specific and obtainable use cases, poor planning will stall an organization’s journey to realized value. Windward’s AIOPs Investment Plan will set the stage to obtain that value in measurable steps.
Your AIOps Investment Plan should increase performance, predict outages, and automate mundane tasks. It should make AIOps analytics reporting actionable, and improve risk management. Organizations already using AI are performing an average of 11.5% better.  The IT industry is buzzing about the role artificial intelligence will play in our future. However, as much as there is buzz, the conversation is also wrought with confusion.
According to recent EMA Radar Report statistics, uses for Machine Learning are increasing rapidly
The EMA Radar Report also lists the top 3 use cases of Machine Learning and AIOps.
AIOps is artificial intelligence for IT Operations
This movement to AI has been coined ‘AIOps’ by Gartner and it refers to the use of artificial intelligence for IT Operations. However, research from Statista shows that machine learning is driving the majority of today’s investments.
Top uses for Machine Learning
Machine learning is playing a large role in risk management, performance analysis, reporting, trading, and automation. But wait, what does automation mean? That feels like a big bucket! Automation refers to the automation of mundane tasks that require human intervention. This includes the use of virtual assistants and chat bots. But it also includes the use of pattern recognition algorithms and distilling alerts into actionable intelligence.
At Windward we believe AIOps is a strategy, not a tool, not an algorithm. This requires deep thinking and understanding of the role that machine learning can play in your organization, a prioritization of initiatives that add early business value, focused investment over time, and an emphasis on hiring talent with machine learning skills. Every great strategy requires a plan so teams know what to execute when. Machine learning can turn into “shiny objects syndrome” if there is no plan in place.
Doug Reece | Client Executive
WINDWARD CONSULTING | Strategic thinking. Real-world results.™