IT teams have been increasing their investments into AIOps initiatives, but a majority of these plans have yet to reach maturity.
According to a new survey from Riverbed, only 12% of AI initiatives have been fully deployed and 62% are still in pilot or development stages.
Despite these projects still largely being in development, 59% of organizations remain confident in their AI strategy, a 7% increase from last year. Additionally, 87% of respondents said that the ROI from AIOps has already met or exceeded expectations, with 53% of leaders and 42% of technical specialists saying AIOps outperformed original goals.
However, only 36% of organizations believe they are ready to operationalize AI, a slight decrease from last year’s survey.
Riverbed found that some of the biggest challenges that organizations face when implementing AIOps include data quality issues, tool sprawl, issues with unified communications, and network performance.
“To unlock the full potential of AI, organizations need more than increased investment – they must close the readiness gap, elevate data quality, and align expectations between leadership and technical teams,” the company wrote in a press release.
Forty-six percent of respondents are fully confident in their data quality, with only 34% rating their data quality as excellent. Most respondents (88%) believe that data quality is critical to AI success.
When it comes to tool usage, organizations use an average of 13 observability tools from 9 different vendors. Ninety-six percent of respondents are currently working on consolidating tools, with 57% of leaders saying this consolidation is already in progress.
Organizations are also dealing with performance issues with their unified communication (UC) tools, with UC issues accounting for 15% of all IT tickets. Business and technical users are spending an average of 42% of their week using UC tools, and 65% say that these tools are very important to daily operations. The biggest issues with UC tools are limited visibility (48% of respondents), inconsistent connectivity (43%), and high support needs (37%).
“There should be no barriers to collaboration across companies orchestrating an AI roll-out and seamless communication is essential,” the company wrote.
Networking performance is also a crucial component for AI success, according to 78% of respondents. Ninety-one percent of respondents say that moving and sharing AI data is critical, and 75% plan to set up a dedicated AI data repository strategy by 2028.
Riverbed’s survey was based on responses from 1,200 business decision-makers, IT leaders, and technical specialists at companies with an average of $2.2 billion in annual revenue, spanning seven different countries.
