Use rules when the process is predictable.
Ordinary automation follows defined instructions: transfer a form submission to a record, notify a person when a status changes, or check whether required fields are present. When inputs and rules are predictable, this can be a clear and useful foundation.
The design still needs reliable integrations, permission to act, and a way to handle errors. Adding AI does not remove those requirements.
Use language assistance for unstructured information.
Language models can help interpret or generate text: summarize a message, classify an inquiry, draft a response, or answer a question using retrieved company material. Their outputs need evaluation because fluent language can contain mistakes.
A practical workflow may combine a model’s interpretation with ordinary rules and human approval. The model does not need unlimited discretion to provide useful assistance.
Use applied machine learning for a defined data problem.
A custom model may be appropriate when the business has a specific predictive or pattern-recognition task and suitable data. Examples include forecasting, detecting unusual events, or classifying records.
Before investing, define the decision the model will support and compare its performance with a meaningful baseline. Data quality, error costs, maintenance, and changes in the operating environment all affect whether the result is useful.
Choose the simplest approach that meets the need.
These approaches can work together. An automation might collect information, a language model might prepare a draft, and a person might approve the action. Another workflow may need no model at all.
- Ask about the input: structured fields, free text, documents, images, or historical data?
- Ask about the output: a record update, a draft, an answer, or a prediction?
- Ask about the consequence: what happens if the system is wrong?
- Ask about the economics: does the improvement justify implementation and operating effort?
Explore WAIV’s solutions or bring us a workflow to discuss the appropriate starting point.