Cisco study says UK firms face soaring observability costs

Cisco has published UK findings showing most IT professionals surveyed said observability costs exceeded infrastructure or operational costs at their organisations this year. The figures come from a study of 300 UK IT operations and engineering professionals.

The research found that 64.7% of UK respondents said observability costs had overtaken infrastructure or operational spending, highlighting pressure on companies as they monitor and troubleshoot increasingly complex IT environments. Half of those surveyed, 50.7%, also said their organisation had faced unexpected costs linked to telemetry data.

These surprise bills appear to be a particular source of operational strain. The survey found that 55% of UK respondents said significantly higher-than-expected charges created more pressure on operations than a high baseline cost for ingesting and storing data.

Rising costs are also changing how some organisations handle monitoring data. Among UK respondents, 38.3% reported reducing data coverage or retention because of higher telemetry costs, suggesting some teams are narrowing what they collect or how long they keep it to manage spending.

AI Pressure

The UK findings sit alongside broader global concerns about the cost of using AI in IT operations. In a wider survey of 2,050 respondents across 10 countries, 55% said they could not control AI costs and 60% said unexpected billing spikes caused more operational strain than high baseline costs.

The report also points to heavy UK use of AI agents for diagnostic work. Some 32% of UK respondents said they use AI agents all the time to diagnose root cause, compared with 20% globally.

At the same time, concern about these systems remains significant. In the UK, 55% said they strongly worry about the unintended consequences of AI agents, while globally 83% of respondents said they were concerned about such consequences.

The international results suggest many organisations see monitoring AI as important but still lack clear ways to judge outcomes. Globally, 87% of respondents consider monitoring AI a priority for their organisation, yet 54% do not have clear business outcomes tied to it. A further 56% said they are unable to measure AI workload metrics such as large language model response quality.

Shared Systems

The report found that 67% of global respondents use a single observability platform to gain a unified view of telemetry costs. Cisco presented this as one way organisations try to identify where spending is arising as the volume of machine-generated data increases.

The findings also show closer working between observability and security teams. Globally, 81% of respondents said monitoring AI workloads had increased collaboration between those functions, while 84% said data sharing between teams had risen.

Jeetu Patel, President and Chief Product Officer at Cisco, said the growth of AI agents will force companies to rethink both oversight and security. "Most companies will soon have far more agents at work than people. Managing agents at scale requires reimagining both security and observability. Have our agents been compromised? Are they doing their job well? In the world of agentic AI, these questions are inseparable, and they're moving at machine speed. This report shows that observability and security data are converging, and that teams need to collaborate more than ever. Common data platforms that help us detect and respond to issues in real time are the key to deploying agents we can trust at scale," Patel said.

Cisco also highlighted a subset of organisations it classifies as leaders in observability practices. The report found these organisations were more likely than others to attribute AI costs accurately, monitor model quality and usage closely, and connect telemetry data to business planning.

Among that group, 91% said they could accurately attribute AI costs, compared with 69% of non-leaders. The report also found they were 2.4 times more likely than non-leaders to say the return on investment from their observability platforms significantly exceeded expectations.

Kamal Hathi, Senior Vice President and General Manager of Splunk at Cisco, said: "For today's enterprises, the excitement of AI is clashing with the reality of the bill. We believe observability is the essential bridge to restoring predictability and confidence to the agentic AI era. By providing the necessary guardrails and incorporating observability into an AI tokenomics framework, leaders can transform AI from an unpredictable expense into a measurable and strategic long-term business investment."