Build an AI service around a problem customers pay to solve
An AI agent needs a useful business role.
Begin with the customer’s work
Find a recurring problem with an identifiable owner. Ask how it is handled, what slows it down, and what the consequence of an error would be. A demonstration is easier to sell when it uses the structure of a real workflow rather than a general promise of productivity.
Choose a delivery model
- A scoped implementation can connect an AI capability to an existing process.
- Managed automation can include maintenance and exception review under an agreed service scope.
- A software product can serve a repeated need across organisations when its permissions and operating model support that use.
- Training can help teams use approved tools and evaluate their output.
Price the complete responsibility
Consider discovery, engineering, external services, review, support, and usage. Clarify which charges are fixed and which depend on volume. A model API bill is only one part of the cost of delivering a reliable service.
Use a paid pilot responsibly
Define one problem, agreed access, success criteria, and a review date. Explain what the pilot includes and what remains manual. Do not promise a financial return without a defensible baseline and a way to measure it.
Build a business that can support the work
The offer needs customer acquisition, delivery ownership, and an operating process after launch. Track whether customers continue using the workflow and whether support demands fit the commercial model. AI creates a capability; the surrounding service determines whether it becomes a sustainable business.