Splunk Report: Over Half of Firms Struggle to Control AI Costs as Agents Drive Bill Volatility
A new Splunk report reveals that 55% of surveyed organizations cannot effectively control AI costs, with 60% finding unexpected bill spikes more financially straining than a consistently high baseline.
According to TechRadar, Splunk's 'State of Observability 2026' report, published on October 22, 2026, claims that AI costs are becoming increasingly unpredictable for businesses as vendors shift toward consumption-based models and agentic AI adoption rises.
The report notes that because agents work independently and consume vast variances in tokens depending on task complexity and model choice, spending fluctuations have become severe. Data shows that more than half (55%) of surveyed organizations say they cannot effectively control their AI costs, while 57% worry that their telemetry monitoring costs exceed the infrastructure being monitored.
Regarding financial pressure, 60% of respondents stated that unexpected spikes in AI bills cause more strain than maintaining a consistently high but flat baseline cost. This highlights the budgeting challenges enterprises face when transitioning from traditional seat-based pricing to dynamic consumption models.
Despite these cost control hurdles, AI has driven positive changes in operational collaboration. 81% of firms reported that monitoring AI workloads increased cooperation between observability and security teams. Furthermore, 91% of observability leaders claimed they could accurately attribute costs to specific models, agents, or workloads, compared to only 69% of non-leaders. Cisco Chief Product Officer Jeetu Patel commented that the report reflects the convergence of observability and security data, necessitating greater team collaboration.