Use a native feature when it already does the job
Start by checking the tools your team uses. If an existing feature handles the task, permissions, and required output, configuration and training may be enough.
Check the actual account and plan. A vendor's feature announcement does not establish that your team has access, that it connects to the required records, or that it supports your approval process.
Use ordinary automation for stable rules
A fixed routing rule, a scheduled export, or a calculation with agreed inputs can often be implemented without asking a language model to decide what to do. Keep known formulas and transaction constraints in deterministic software.
The useful test is whether the next step can be specified reliably from structured inputs. If it can, a simpler workflow may be easier to test and maintain.
Consider an agent for varied inputs and bounded choices
An agent may help when incoming requests differ, context lives in several approved sources, or the next step depends on interpreting that context. It still needs a permitted tool set, defined stopping rules, and an owner for exceptions.
For example, an agent could read a customer request and prepare a structured handoff. Ordinary code could validate the fields and check for duplicates. A staff member could approve the reply. The workflow can use all three without giving the agent unrestricted control.
Compare the complete workflow
Before deciding, write down the trigger, available inputs, required outcome, and decisions reserved for people. Then compare:
A solution that produces a convincing draft but leaves every handoff manual may not address the original problem.
- Access: Can the proposed approach read and update the required records with authorization?
- Reliability: What happens when an input is missing or a tool is unavailable?
- Review burden: How much time will staff spend checking and correcting the work?
- Operating cost: Which usage charges, software licenses, and maintenance responsibilities recur?
- Ownership: Who can pause, change, or support the workflow after launch?
When to pause the project
Pause if no one owns the process, if required access is unavailable, or if the proposed system would make commitments without an authorized reviewer. Resolve contradictory source information before treating the output as reliable.
An early version should be small enough to test, but the service is not limited to a single pilot. Expansion depends on what the workflow needs and what the evidence supports.
Get help with the choice
Read about AI agent implementation in Rhode Island, explore workflow examples, or discuss the work you want to improve.
Common questions
Is every chatbot an agent?
No. A conversational interface may only return an answer. An agent workflow can also use approved tools to gather information or perform an action. Define the actual behavior rather than buying the label.
Do we need multiple agents?
Only if separate roles solve a specific problem. More agents also mean more handoffs to test and operate. A single agent or ordinary software may be sufficient.
How should we measure whether it helps?
Compare completed work and total handling effort, including review and corrections, against the starting process. Also track failures and exceptions. More generated output does not necessarily mean less work.