AI CONSULTING & AUTOMATION / A PRACTICAL ANSWER
What determines the cost of an AI integration?
The short answer
AI integration cost depends on the workflow around the model: data preparation, system connections, evaluation, permissions, review and maintenance. The model call itself may be only one component. Ask for a scope that distinguishes investigation, pilot implementation and the responsibilities of operating a wider release.
What to establish
Map inputs, destinations and required access. Identify whether existing systems offer suitable interfaces and who can approve their use. Include representative test cases, error handling and the work needed to prepare or clean information before a useful result can be produced.
How to assess readiness
Compare recurring provider charges with review effort, support and change management. Do not infer savings from generation speed alone. Ask how usage limits, exceptions and future updates will be handled, and which unknowns require a discovery stage before they can be priced responsibly.
ILLUSTRATIVE EXAMPLE / NOT A CLIENT RESULT
Make it concrete.
A document workflow may need substantial effort to establish reliable input formats and route reviewed outputs into the right system. Quoting only the cost of generating a summary would leave much of the real integration work unaccounted for.
Before you commission
- Separate discovery, pilot and operating costs.
- Include data and integration dependencies.
- Estimate review, maintenance and exception handling.
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FROM THE QUESTION TO THE WORK
A useful next step.
Bring the decision, the existing situation and the information you have. We can help define a scope before you commit to a wider project.
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