Riverbed Survey Reveals Enterprise Push for Agentic AI in Autonomous IT Operations, Despite Trust Concerns

Riverbed, a leader in AIOps for observability, today announced the findings of its "State of Autonomous IT Operations" global survey, revealing a strong enterprise desire to leverage agentic AI for autonomous IT operations. The survey indicates that 90% of organizations aim to use agentic AI to drive autonomous IT, with 76% considering it central to their future IT strategy. Furthermore, 91% of respondents reported that their AI investments have met or exceeded expectations. Despite this enthusiasm, a significant hurdle remains: 77% of organizations are hesitant to allow AI to make operational decisions without human approval. This reluctance stems from concerns about security and compliance (55%), the risk of operational disruption (45%), and a general lack of trust in AI decisions (39%). Consequently, 92% of those surveyed believe that AI observability and governance will become a critical new IT domain. This trend aligns with the broader industry movement towards more intelligent and self-managing IT environments. AIOps platforms have evolved beyond basic anomaly detection and alert correlation to encompass automated remediation and predictive capabilities. The increasing complexity of cloud-native, hybrid, and distributed architectures makes manual IT operations unsustainable, driving the need for AI-powered solutions that can predict and resolve issues proactively. However, the survey underscores that simply deploying AI is not enough; organizations must also establish robust frameworks for AI governance and observability to build confidence in autonomous systems. This includes ensuring transparency in AI's decision-making processes and providing mechanisms for human intervention and oversight. In practice, this means that while the promise of fully autonomous IT is compelling, practitioners should focus on a phased approach. Initial implementations of agentic AI should prioritize use cases where human oversight can be easily integrated, allowing teams to gradually build trust in the AI's capabilities. Investing in AI observability tools that provide clear insights into AI behavior, performance, and decision paths will be crucial. Furthermore, developing clear policies for AI governance, including defining roles and responsibilities for human-in-the-loop interventions, will be essential for successful and secure adoption of agentic AI in IT operations.