Automation Buying Guide
AI Automation Cost: How to Price a Real Business Workflow
AI automation cost is driven less by the model itself than by the workflow around it: systems, exceptions, permissions, data quality, human approvals and maintenance. A simple email workflow and a multi-system operational agent are very different projects.
What makes an automation simple or complex?
- Number of systems and integrations involved
- Quality and structure of the incoming data
- Volume and frequency of cases
- Number of exceptions and approval paths
- Need for audit logs, permissions or sensitive-data controls
- Monitoring and maintenance after launch
Prototype first when the workflow is bounded
When one workflow is clearly defined, a fixed-scope sprint can be more efficient than a large consulting engagement. The goal is to map the current process, define the architecture, build a first working version where access allows, and document the path to production.
NLG's current AI Automation Sprint is €1,250 excluding VAT for one bounded workflow, with no ongoing commitment. It is designed as a first implementation step, not as a promise that every automation can be completed for the same price.
Do not ignore operating cost
The true cost includes model usage, automation tooling, integrations, monitoring, maintenance and human review. A cheap workflow that constantly fails or requires manual rescue can cost more than a better-designed system.
Before scaling, measure cycle time, capacity, quality and exception rate against the original process.
When a larger implementation is justified
Larger projects make sense when multiple teams, systems or compliance requirements are involved, or when the automation becomes part of a core business process. In that case, discovery, testing, governance and rollout need a wider scope.
Key takeaway
Price the workflow, not the buzzword. Start bounded, measure the result, then expand only when the operating model is proven.