BigPanda, the Agentic ITOps platform for enterprise IT, today announced new research conducted by independent research firm UserEvidence, revealing that enterprises spend an average of $5.36 million annually on IT operations support outsourced to global systems integrators. The report, The High Cost of Low-Quality L1 NOC Outsourcing, finds quality issues, SLA breaches, and contract overages — and growing openness to a new operating model.
The research points to an operating-model problem, not a provider-quality one: adding more providers and outsourced staff doesn't address the underlying issue — a model that continues to produce misrouting, rework, and service risk regardless of who runs it.
The report found that 34% of level 1 issues are misrouted — meaning a ticket lands on the wrong desk, compounding the average 34 minutes it already takes to route each issue. Another 24% are resolved incorrectly or require rework, so the same issue is addressed by the team that closed it prematurely and again by whoever has to reopen it.
That's not just wasted effort — it's time for problems to quietly worsen while they sit "resolved" on paper, but broken in practice. Critically, 94% of survey respondents reported service-level agreement breaches caused by poor outsourced ITOps performance.
"Enterprise ITOps is manual, reactive, and expensive. For twenty years, the answer to increasing IT complexity and scale was more people, more outsourced labor, and more GSI contracts," said Assaf Resnick, Founder and CEO of BigPanda.
"That math doesn't work anymore, and this data proves it," Resnick continued. "If spending more and adding providers still produces the same errors, the problem isn't capacity. It's the operating model."
Respondents reported handling approximately 25,000 L1 NOC incidents per month, with nearly one in five respondents reporting at least twice that volume. They also reported using an average of 19 monitoring and observability tools to manage the load, while 23% said they use 25 or more.
That pressure is compounding as AI-generated code and AI-managed infrastructure accelerate change in production environments, widening the gap between machine-speed change and human-speed IT operations.
The provider model is similarly fragmented: 79% of respondents said their organizations outsource ITOps support to two or more GSIs. Ninety percent also reported unplanned expansion, overage, or true-up charges, which added an average of 30% to annual contract costs.
"The current model isn't built to survive what's coming," Resnick said. "AI-native code development, hybrid cloud, and microservices have made environments faster-moving and more fragmented every year, and ITOps won't be able to keep pace."
The research indicates that IT leaders are ready to consider that change, with 92% of respondents saying they are open to evaluating or piloting alternatives to their current ITOps approach. The opportunity is not to eliminate human expertise, but to reserve it for incidents and decisions that require judgment while automation handles routine, repeatable work.
The BigPanda Agentic ITOps platform uses specialized AI agents grounded in the BigPanda IT Knowledge Graph, a continuously learning system of operational context. BigPanda L1 Agent applies that context to detect, triage, and resolve incidents while reserving human expertise for work that requires judgment. The research surveyed 112 U.S.-based IT leaders at global enterprise organizations who work with global systems integrators.
About BigPanda
BigPanda delivers the operational intelligence layer for Agentic ITOps. We enable enterprises to keep the digital world running by transforming manual and reactive human processes into intelligent, autonomous systems that detect, respond, and prevent IT incidents at machine speed. That’s why the world’s most trusted brands rely on BigPanda to improve operational efficiency and deliver exceptional service reliability to their customers.
