More Than Half of It Teams Lag in Adoption of Artificial Intelligence for Datacenter Operations
Trace3, a leader in business transformation solutions, released the results of a new survey showing that 76 percent of IT teams have not yet implemented artificial intelligence technologies to improve datacenter operations, despite the benefits of AIOps for business efficiency.
Even more concerning, just 20 percent of IT managers who have implemented AIOps in the past year say they have achieved value from their investments. That compares to 38 percent who have not yet recognized value from AIOps, and 42 percent who say the extent of value from AIOps remains unclear.
Artificial Intelligence for IT Operations, known as AIOps, has emerged as a powerful tool for IT teams to automate datacenter processes by combining big data, machine learning and visualization tools. Infrastructure and operations leaders implement AIOps platforms to reﬁne their current performance analyses. Over the next ﬁve years, the goal will be to further augment IT service management and automation.
The Trace3 survey reveals that most IT leaders are still struggling to implement effective strategies for AIOps due to a lack of clarity about their own technology expectations and business objectives, according to David Ishmael, Trace3 Vice President of Operations Analytics.
“All too often, the promise of new technology gets way overhyped,” Ishmael said. “Business leaders should always set clear expectations to define the metrics of project success before rolling out new technology solutions, and an AIOps project for the datacenter is no different.”
Though the global AIOps growth rate is projected at approximately 34% through 2025, a large proportion of survey respondents have not yet invested at all, or have invested very little, in AIOps. Just over half of survey respondents (51 percent) have no budgets planned for AIOps projects in the next one to three years. Another 21 percent expect to spend less than $100,000 in that period, while 22 percent expect to spend $100,000 to $1 million on AIOps over the next one to three years.
The biggest inhibitors to achieving AIOps success for survey respondents involves a lack of relevant staff skills (25 percent); a lack of a coherent AIOps strategy (21 percent); an inability or inexperience to adopt machine learning strategies (20 percent); and shortfalls in data processing quality and data storage capacity (19 percent).
Other Key Findings:
- The primary IT concern to be solved by an AIOps platform is threat detection and analysis (34 percent), followed by resource utilization (24 percent), and storage management (17 percent).
- The top IT operations capabilities that respondents hope to improve from operational analytics include systems automation (28 percent), business intelligence (26 percent), and data lake and data warehouse management (14 percent).
- The top focus areas for driving AIOps insights over the next three to five years include improving IT operations (34 percent), application performance management (27 percent), and network performance management (21 percent).
Trace3 conducted this AIOps survey by gathering online responses from 160 CXOs, VPs, directors and mid-level executives from IT, security, business and operations teams in the U.S. during March/April 2019.