The most useful question is not “Which AI should we buy?” It is “Which repeated task already has a clear input and output?”
Keep observation separate from interpretation. Write down what happened first—time, source, stage, outcome—then add the explanation. That prevents the story from changing to fit the result.
Research and summarization
AI can reduce time spent turning public information into account notes, drafts or meeting preparation.
For “Research and summarization,” put a human review step at the point where an error could reach a customer, supplier or public page. Automation should reduce repetition, not remove accountability.
Drafting and variation
First drafts of outreach, FAQs and internal documentation can speed up when a human reviews accuracy and tone.
For “Drafting and variation,” keep the request honest and the response specific. Manufactured praise is less useful than a detailed account of what actually happened.
Classification
Lead notes, support tickets and inquiry types can be sorted when categories are well defined.
For “Classification,” use medians, ranges and reason codes where they help. One unusually large order or one terrible day can distort an average and create a false sense of certainty.
Risk areas
Customer promises, legal interpretation, safety guidance and unverified personal data need stronger human control.
For “Risk areas,” keep the field definitions beside the spreadsheet. A metric that changes meaning between team members is not comparable data.
Adoption test
If the team cannot explain the process without AI, automating it may hide confusion rather than solve it.
For “Adoption test,” put a human review step at the point where an error could reach a customer, supplier or public page. Automation should reduce repetition, not remove accountability.
How to collect evidence
For this article, create a short table with a fixed definition for each field, collect it over a defined period, and keep the raw observations. Add interpretation after the sample exists, not before.
How to keep the report honest
For this article, label internal samples as internal, note the date range and definitions, and keep claims proportional to the evidence. If a number comes from a public source, verify that the population and period actually match the decision you are making. For this topic, the first things I would put on that review are research and summarization, drafting and variation.