DevOps / SRE / Platform · 25.08.2026, 19:16 UTC
How telemetry pipelines keep AI agent costs under control
| Schweregrad | info |
|---|---|
| Kategorie | DevOps / SRE / Platform |
| Quelle | The New Stack ↗ |
| Veröffentlicht | 25.08.2026 UTC |
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As enterprises move from experimenting with AI to running autonomous agents in production, an infrastructure problem is emerging: rising telemetry costs. Non-deterministic, iterative, and capable of generating data at machine speed, agents are far harder to monitor — and their costs far harder to predict — than conventional applications.
Many companies are struggling to attribute and defend their telemetry bills. In fact, 59% of organizations have already terminated or delayed an agentic AI deployment due to monitoring costs, according to a survey of more than 300 enterprise IT decision-makers in North America and Western Europe, commissioned by Apica and conducted by Omdia/Informa TechTarget.
The agents most affected are often in some of the most high-stakes deployments: think cybersecurity, compliance, and fraud detection. As monitoring bills explode, deployments aren’t necessarily getting killed by engineering teams. More often than not, it’s finance pulling the plug.
Andi Mann, chief product and technology officer at Apica, recently saw this play out at a large bank. The organization couldn’t pin down exactly what it was spending on its AI programs.
“They knew they couldn’t afford to keep going on the same trajectory, so they had no choice but to cancel certain AI programs,” Mann tells The New Stack. “It’s a pattern I have seen before, because AI projects are cannibalizing typical budgets.”
“It’s a pattern I have seen before, because AI projects are cannibalizing typical budgets.”
The implications are huge. As people, funding, and monitoring resources are …