According to EMA, “AIOps is largely successful, returning very high value relative to cost in 80% of the implementations and at least paying for itself in all cases.”
Though AIOps is still considered early as an IT initiative, many enterprises realize that automation and artificial intelligence (AI) are closely linked and are the primary catalysts for digital transformation.
Think about the rapid advances in big data, AI and machine learning (ML), as well as the growing use of cloud computing, microservices and containers. You need an efficient means to address resulting operational complexities so you have more time to spend on initiatives that drive your business.
“AI(work)Ops 2021: The State of AIOps” takes a ground-level look at the AIOps experience. Focusing on groups that were most successful, it examines the top use cases, capabilities, drivers, challenges, results and rewards of AIOps implementations, as well as buying considerations when it comes to selecting a new AIOps platform.
More than 2,500 global participants were screened to vet the final field of 200+ IT practitioners for insights into how AIOps is being used now and in the future. Perhaps the most surprising finding was the extent of AIOps success, as the vast majority of respondents realized high value relative to cost, showing that AIOps exerted a sometimes-transformative impact on the relationship between IT and the businesses it serves.
What’s driving your need for AIOps?
See how your business compares to others in relation to the use cases and capabilities driving AIOps adoption (e.g., observability, incident resolution, application performance management (APM) and network performance management, just to name a few). Get a sense of why flexibility, scalability and extensibility are critical characteristics for every platform, for every organization.
Evaluate your need for AIOps