How to choose your first AI use case in Salesforce

Describe the work before choosing the technology

Ask a colleague to walk through the last real instance of the problem. Where did they search? What did they copy between screens? What judgement did they make? What happened when information was missing? These details turn “we need an AI assistant” into a process that can be improved.

A useful candidate might be preparing a case summary before a service handoff. The start is a case entering a queue; the finish is a reviewer accepting a briefing with open questions and source references. “Handle customer service” leaves too many decisions undefined.

Use five questions to compare candidates

Treat a missing answer as work to do, rather than assigning an optimistic score. A high-volume task can still be a poor first choice if nobody can establish the correct answer.

A worked example: preparing a service handoff

Illustrative scenario. A service coordinator reads case notes and recent correspondence before handing work to a specialist. The proposed agent prepares a short briefing: the request, what has already been tried, outstanding information and the next question. It does not close the case or promise a resolution date.

The team supplies representative cases, agrees which information the reviewer needs and checks whether the briefing is supported by the records. Success means a useful handoff with less total preparation and correction work. The pilot should also show what happens when correspondence conflicts or a relevant record is inaccessible.

Check whether a simpler change would solve it

If the problem is a missing required field or a known routing rule, start by assessing a form change, report or Salesforce Flow. AI becomes more relevant when the work involves interpreting variable language or assembling a readable explanation. Anthropic’s engineering guidance recommends beginning with the simplest workable approach; adding an agent introduces cost and latency that need a purpose. [1]

Turn the choice into a short pilot brief

Write down the trigger, input records, expected output, permitted actions, reviewer and acceptance criteria. Include exclusions: no outbound messages, for example, or no changes to eligibility decisions. Identify who supplies sandbox access and who resolves data questions.

REDA works with your team to scope a focused sandbox pilot around that process. REDA AI supplies configurable assistance and tools; your data model and procedures shape the implementation. The first decision is whether the workflow earns a production plan, not how many agents you can create. See the pilot journey.