Artificial intelligence can enter a business through very different tasks. Preparing a first summary, classifying documents, and suggesting answers require different levels of control. Before choosing a tool, you need to define which activity you want to improve.
A practical proposal is to start with a circumscribed and reversible task. For example, a system can help prepare a draft response to a frequent request, leaving a person to verify before sending. The result should also be evaluated for correctness and utility, as well as for speed.
The comparison should include the time needed to check and correct the output. A quickly produced text may require a lengthy review if it contains inaccurate information. It is useful to collect recurring errors and cases in which the system does not have the necessary data.
It is also necessary to establish what information can be used in the tool, who can access it and how it is managed. These choices depend on the characteristics of the service and the context of the company: they cannot be solved by a generic declaration of reliability.
OECD research on the digital transformation of SMEs recalls the role of skills in technology adoption. In the proposed project, the training serves to understand when to accept a proposal, when to correct it and when to interrupt the process. Adoption makes sense when it improves a concrete outcome without shifting costs and problems to those who need to control it.