AI pilot budgets often underestimate the true cost of bringing models to production. Understanding these hidden costs helps set realistic expectations.

Ground Truth

Building labeled training data is expensive and time-consuming. Expect to spend 40-60% of your time on data preparation before you can even train a model.

Eval Metrics

Define evaluation metrics that align with business outcomes, not just model accuracy. You need metrics for fairness, bias, and error types that impact users.

Guardrails

Implement safety controls early. Model monitoring, drift detection, and failover mechanisms have ongoing operational costs that must be factored into budgets.

Infra

Production AI infrastructure costs scale differently than prototypes. GPUs, storage for large datasets, and serving infrastructure can dwarf development costs.

Value Tracking

Measure actual business value, not model metrics. Track KPIs like customer satisfaction, revenue impact, or cost reduction to prove ROI.