Agentic AI budgets are rarely blown by the model. They are blown by integrations, evaluation, guardrails and run costs nobody estimated. Here is where the money goes.
Integrations, workflow design, approval points, evaluation and guardrails.
Inference, monitoring, re-evaluation on change and human review time.
Phase the rollout, right-size models per step, and gate releases on evaluations.
Agentic AI cost has two halves: what it takes to build an agent you can trust, and what it takes to run it every day. Proposals often price the first and ignore the second.
Weighing a platform against a custom build? See buy vs. build for enterprise AI, and our buyer’s checklist for agentic AI partners.
Usually integrations with existing systems, followed by evaluation and guardrail work — not the model itself.
Inference spend, re-evaluation whenever models, prompts or tools change, human review of approvals and escalations, and monitoring and support.
Use smaller models for routine steps, reserve larger models for complex reasoning, cache repeated context and results, and track spend per workflow.
Yes — one workflow with clear success metrics, approval points and an evaluation plan, then scale what proves itself.