There is no single meaningful price for building an AI agent without a defined scope. Estimate the work required to design the task, connect data and tools, implement execution controls, evaluate results, and prepare deployment. A limited internal assistant and a system that changes business records involve different amounts of integration and verification work.
Initial build budget = implementation + integration + evaluation + deployment setup.
Build the estimate from activities and assumptions. List the expected implementation effort, data preparation, connection setup, and test development. Add the work needed to handle failures and support the system after launch. Use your team's actual labor assumptions and current supplier quotes rather than copying a headline estimate from a different project.
Separate the initial build from ongoing operation. Model calls, tool services, hosting, and human review can continue after the first version is complete. If an existing product covers the task, compare the effort of configuring and evaluating it with the effort of maintaining custom software. A short prototype can expose integration gaps before you commit to a broader implementation.
Present a range with explicit reasons for uncertainty, such as an undocumented data source or an unresolved approval requirement. Define what the budget includes and what would count as a scope change. The useful estimate is one that can be revised as evidence arrives. It should not imply a guaranteed cost or return, and it should not treat a successful demonstration as proof that production deployment requires no further work.
Source: Anthropic, Building effective agents, for scope and evaluation principles. This is a budgeting method; no supplier price is asserted.
